Landscape Ecol (2011) 26:225–237
DOI 10.1007/s10980-010-9556-0
RESEARCH ARTICLE
Fire severity and seed source influence lodgepole pine (Pinus
contorta var. murrayana) regeneration in the southern
cascades, Lassen volcanic National Park, California
Andrew D. Pierce • Alan H. Taylor
Received: 15 June 2010 / Accepted: 8 November 2010 / Published online: 20 November 2010
Ó Springer Science+Business Media B.V. 2010
Abstract Rocky Mountain lodgepole pine, (Pinus
contorta var. latifolia) regenerates quickly after high
severity fire because seeds from serotinous cones are
released immediately post-fire. Sierra lodgepole pine
(P. contorta var. murrayana) forests burn with variable
intensity resulting in different levels of severity and
because this variety of lodgepole pine does not have
serotinous cones, little is known about what factors
influence post-fire regeneration. This study quantifies
tree regeneration in a low, moderate, and high severity
burn patch in a Sierra lodgepole forest 24 years after
fire. Regeneration was measured in ten plots in each
severity type. In each plot, we quantified pre- and postfire forest structure (basal area, density), counted and
aged tree seedlings and saplings of all species, and
measured distance to the nearest seed bearing tree.
There was no difference in the density of seedlings and
saplings among severity classes. Distance and direction to the nearest seed bearing lodgepole pine were the
best predictors of lodgepole seedling and sapling
density in high severity plots. In contrast to Rocky
Mountain lodgepole pine, regeneration of Sierra
lodgepole pine appears to rely on in-seeding from
A. D. Pierce (&) A. H. Taylor
Department of Geography, Pennsylvania State University,
302 Walker Building, University Park, PA 16802, USA
e-mail: adp179@psu.edu
A. H. Taylor
Earth and Environmental Systems Institute, 302 Walker
Building, University Park, PA 16802, USA
surviving trees in low or moderate severity burn
patches or live trees next to high severity burn patches.
Our data demonstrate that Sierra lodgepole pine
follows stand development pathways hypothesized
for non-serotinous stands of Rocky Mountain lodgepole pine.
Keywords Lodgepole pine Fire severity Stand
replacing fire Tree regeneration Dispersal distance Seed dispersal Safe sites Stand development
Introduction
High severity disturbance that kills most or all of the
forest canopy is often followed by a pulse of tree
establishment that leads to the development of an evenaged forest (Agee 1993; Gutsell and Johnson 2002).
This post-fire regeneration pattern is exemplified in
stands of Rocky Mountain lodgepole pine (Pinus
contorta var. latifolia) where the pines have serotinous
cones (Turner et al. 1997, Despain 2001). However,
Rocky Mountain lodgepole can regenerate without fire
in tree fall gaps and forms self replacing stands on some
sites (Despain 1983). Moreover, there is evidence that
cone serotiny varies among stands and that the degree
of cone serotiny contributes significantly to both the
abundance of post-fire regeneration immediately postfire and how lodgepole pine forests develop following
fire disturbance (Turner and Romme 1994; Turner et al.
1997; Nyland 1998). Consequently, variation in cone
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226
serotiny is thought to lead to distinct pathways of
lodgepole pine forest development (Turner et al. 1997;
Nyland 1998). Nyland (1998) hypothesized several
stand development pathways for lodgepole pine
depending on both degree of serotiny and percent
mortality. In stands dominated by serotinous lodgepole
pine, a single pulse of regeneration develops into a
closed canopy of even-aged lodgepole pine (Nyland
1998). In stands without serotinous cones, post fire
regeneration is thought to be regulated by local seed
rain and short distance (\60 m) dispersal (Nyland
1998). Thus, large and severe burns, even those with
small numbers of surviving mature trees, may take
decades to centuries to develop into closed forest
following fire resulting in multi-aged stands (Nyland
1998).
In the upper montane zone of the southern Cascade
range, Sierra lodgepole pine (Pinus contorta var.
murrayana; hereafter lodgepole pine)1 grows in
monospecific and mixed stands with red fir (Abies
magnifica var. magnifica), white fir (A. concolor), and
Jeffrey pine (P. jeffreyi) on both the western and
eastern slopes of the range at elevations between
1900 and 2200 m (Franklin and Dyrness 1973; Parker
1991; Barbour and Minnich 2000). Lodgepole does
not have serotinous cones in the southern Cascade
Range or the Sierra Nevada and therefore the role of
fire in the development and dynamics of lodgepole
forests in these mountains is not well known (Lotan
and Critchfield 1990; Despain 2001). In the southern
Sierra Nevada, Caprio (2008) found fire scar evidence of extensive surface fire at intervals of 50 years
(mean Fire Return Interval [FRI]) in self-replacing
lodgepole forests. The fires were intense enough to
scar trees, but the fire regime was interpreted as one
of low and moderate severity with stands that were
mainly multi-aged (Caprio 2008). In the southern
Cascades, lodgepole occurs in nearly pure stands on
moist valley bottoms and flats characterized by coldair drainage and nutrient-poor soils (Franklin and
Dyrness 1973; Zeigler 1978; Parker 1991). Lodgepole are both even- and multi-aged and also display
negative exponential size structures (Zeigler 1978;
Parker 1993). In Crater Lake National Park (CLNP,
approx. 300 km north), lodgepole exists in self
replacing communities or as a post-fire colonist that
1
All nomenclature follows Hickman (1993).
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Landscape Ecol (2011) 26:225–237
will succeed to forests of more shade-tolerant
species—primarily red fir (Zeigler 1978; Chappell
and Agee 1996). In Lassen Volcanic National Park
(LVNP) and the surrounding Lassen National Forest,
several authors have described fire regimes in lodgepole stands (Parker 1993; Taylor and Solem 2001;
Bekker and Taylor 2001). Lodgepole pine stands
experienced more high severity fire than adjacent
forest types (38–75% high severity vs. 13–25%), and
the interval between fires was longer (median FRI 67
vs. 41 years) (Taylor and Solem 2001). Bekker and
Taylor (2001) confirm these findings and describe
lodgepole pine stands that burned at long intervals,
but with high severity and large extent. In contrast,
the regeneration dynamics of lodgepole pine stands in
LVNP appear to be driven by both tree fall gap
disturbances and fire (Parker 1993).
The effects of variable intensity fire on the abundance of post-fire regeneration of lodgepole in the
Cascade Range is poorly known but regeneration is
thought to be abundant following high intensity fire
(Franklin and Dyrness 1973; Zeigler 1978). Yet, in
contrast to Rocky Mountain lodgepole, Chappell and
Agee (1996) found that categories of fire severity were
not related to the abundance of post-fire lodgepole
seedlings and saplings in CLNP. The high-severity
post-fire environment may be less favorable than in
mature forest, or seed sources may be too distant for
the establishment of an abundant seedling population
immediately following fire (Zeigler 1978; Chappell
and Agee 1996). In CLNP lodgepole pine forests
seedling density was negatively related to distance to
seed sources (Chappell and Agee 1996). Further,
because lodgepole pine cones develop in one year,
shed their seeds in the second year, and viable seeds
germinate in the third year (Lotan and Critchfield
1990), variation in snowpack depth and amelioration
of abiotic conditions by safe microsites provided by
shrubs and herbs are thought to be key factors
contributing to successful post-fire lodgepole pine
regeneration (Zeigler 1978; Chappell and Agee 1996).
The goal of this study was to identify factors that
influence post-fire regeneration in lodgepole pine
stands in the southern Cascades within the perimeter
of the 1984 Badger Fire. Specifically we address the
following research questions: (1) Is the abundance of
tree regeneration related to variation in fire severity?
(2) In high severity patches, is the abundance of
lodgepole regeneration related to the distance and
Landscape Ecol (2011) 26:225–237
direction to the nearest seed bearing tree? (3) Is the
abundance of tree regeneration related to safe
microsites provided by logs, shrubs, or other ground
cover that are known to influence tree regeneration in
similar ecosystems? (4) Is there evidence of an effect
of interannual climate variation on the timing or
number of regenerating individuals?
Methods
Study area
LVNP lies at the southern end of the Cascade Range, a
volcanic plateau punctuated by high volcanic peaks
(Fig. 1). LVNP itself is underlain by recent (Pliocene
to Quarternary) andesites, rhyolites, and basalts (Kane
1980). Dominant vegetation communities covary with
elevation (Parker 1986, 1991, 1993; Taylor 1990,
2000; Schoenherr 1992). High elevation forests are
dominated by mountain hemlock (Tsuga mertensiana)
and whitebark pine (Pinus albicaulis) often with pine
mat manzanita (Arctostaphylos nevadensis) in the
understory. Upper montane forests are composed of
red fir (A. magnifica var. magnifica), white fir (A.
concolor), and western white pine (P. monticola) with
pine mat manzanita (A. nevadensis), greenleaf manzanita (A. patula), and snowbrush (Ceanothus velutinus) in the understory. Lodgepole pine (P. contorta
spp. murrayana) occupies low lying depressions in the
upper montane zone where cold air drainage is a
dominant part of the regeneration climate often with
rabbit bush (Chrysothamnus naseousus) in the understory. Lower montane forests are dominated by
Jeffrey pine (P. jeffreyi) and white fir (A. concolor).
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Fires in LVNP occur mainly during the fall, after
tree growth for the year has ceased (Taylor 2000).
Point fire return intervals in LVNP vary with
elevation and forest type: 16 years in low elevation
Jeffrey pine forest to 22 years in mid-elevation white
fir/red fir forest and up to 70 years in upper montane
red fir-western white pine forest (Taylor 2000). Fire
frequency declined dramatically after 1905 when a
policy of suppressing fire was implemented on
federal forest lands (Taylor 2000).
The climate is Mediterranean and is characterized
by hot, dry summers and cold, wet winters. Average
monthly temperatures at Manzanita Lake, California
(in LVNP), range from -6.6°C minimum and 5.0°C
maximum in January to 7.5°C and 26.1°C in July
(WRCC 2009). Annual average precipitation is
104 cm, but inter-annual variability is high. Most
precipitation ([80%) falls as snow between November and April and annual maximum snowpack depth
(usually in April or May) ranges from 1.63 to 8.41 m
with an average of 4.63 m.
The Badger fire burned 563 hectares with variable
severity near the northern boundary of LVNP in 1984.
This fire was left to burn inside the Park boundary, but
was suppressed when it crossed out of the Park onto
National Forest lands. The area dominated by selfreplacing stands of lodgepole pine before burning
tended to be dominated by high severity effects. Since
1984, some areas have had no successful tree
regeneration while other areas have abundant regeneration of lodgepole pine, Jeffrey pine, white fir and
red fir (Fig. 2). Andesite and basalt of Quarternary age
underlie the area, but surface material is mixed and
includes significant amounts of gravel sized pumice.
The topography is mostly flat to low relief.
Fig. 1 Map showing Lassen Volcanic National Park and its location in northeastern California
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Fig. 2 A photograph of Badger Flat inside Lassen Volcanic National Park showing part of the area of severe burning in P. contorta
dominated stands. Note the patchiness of regeneration
Fire severity patch mapping
Patches that burned at different fire severities were
identified and mapped using aerial photographs, fire
perimeter maps, and a vegetation cover type map in a
GIS. A perimeter map of the 1984 Badger Fire was used
to delimit the boundary of the study area. Recent fire
perimeters from prescribed fires that overlapped the
Badger Fire were used to exclude some areas from
sampling. The vegetation cover type map was then used
to identify the location of the lodgepole dominated area
inside the Badger Fire perimeter. Fire severity patch
types were delimited on 2005 aerial photographs based
on a visual estimate of canopy loss between pre- and
post-fire images. We defined severity patches based on
observed canopy loss: C75% in high severity patches;
between 25 and 75% in moderate severity patches; and
\25% in low severity patches. Patches were visited
once each to ensure that they fell into the above defined
severity categories before sampling began. The minimum mapped patch size was 2.5 ha.
Current stand size structure was identified during
the summer of 2008 by randomly selecting one patch
from each severity class and sampling 10 randomly
located circular plots of 250 m2 in each patch
(n = 30). All trees (dbh C 4 cm) rooted in the plot
were identified to species and their dbh and status (live,
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standing dead [snag], or down and dead) was recorded.
The presence or absence of cones on live lodgepole
pine trees was also recorded. Any dead trees having
most of their bark remaining or still having needles
were recorded as having survived the 1984 fire. All
trees were later categorized into 10 cm size classes.
Post-fire regeneration
Post-fire regeneration was assessed by counting
saplings (\4 cm dbh, C1.4 m height) large seedlings
(0.5–1.4 m height), and small seedlings (\0.5 m
height, C2 whorls) of each species in each quadrant
of the circular plot. Temporal variation in recruitment
was determined by estimating stem age by counting
the number of branch whorls on each stem. We also
cored to the pith all trees with low whorl counts
(B25) and regular growth form which likely regenerated after the 1984 fire. All cores were taken at a
height of 30 cm. To assess the accuracy of whorl
counts and to estimate the number of years needed for
seedlings to reach coring height, we randomly
selected 20 open grown lodgepole pine seedlings at
least 30 cm tall and then cut them off at ground level.
In the lab, discs were removed at the stem base and at
a height of 30 cm. Discs were dried, sanded to a high
polish, and their age was determined by counting
Landscape Ecol (2011) 26:225–237
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their annual growth rings. Cores were sanded to a
high polish and cross-dated to the Lemon Canyon
chronology (Holmes and Adams 1981) using standard dendrochronological techniques (Stokes and
Smiley 1996). The year of the inner most ring was
then used as an estimate of tree age at coring height.
The year of establishment for the seedlings, saplings,
and post-fire trees was estimated by adding a correction
factor to whorl and ring counts based on dated discs
from the sampled seedlings and the tree core ages. We
calculated the average difference between ring count at
ground level and both the ring count at 30 cm and the
total whorl count. For seedling and sapling ages, the
field based whorl count was corrected by adding the
average difference between the basal ring count and the
total whorl count. The age of a cored tree was corrected
by adding the average difference between the basal ring
counts and the ring count at 30 cm.
Spatial patterns and dynamics
To assess the spatial relationship between seed source
and regeneration, we took additional measurements
in 8 of the 10 high severity plots that contained no
seed bearing lodgepole pine stems. From the plot
center, we measured the distance and direction to the
nearest cone bearing lodgepole pine. To determine if
the directions to the cone bearing individual were
randomly distributed, we compared observed directions to a uniform distribution using Kuiper’s Test of
Uniformity (Jammalamadaka and SenGupta 2001;
Agostinelli 2009). We also obtained wind direction
data for Manzanita Lake, CA (7 km west) from the
Remote Automated Weather Stations (RAWS)
archive maintained by the Desert Research Institute
(DRI 2010) to compare the direction of cone bearing
individuals to dominant wind directions using a
circular version of a correlation test (Jammalamadaka
and SenGupta 2001; Agostinelli 2009).
We investigated the relationship between regeneration density and distance to seed source by applying
an exponential dispersal kernel (Willson 1992).
Assuming that the density of seedlings and saplings
in each plot would decay exponentially with distance,
we used the linear form:
lnð yÞ ¼ lnðaÞ bx
ð1Þ
where y is the count of seedlings and saplings and x is
the distance to the nearest cone bearing individual
(Willson 1992). To investigate the relationship
between regeneration age and distance, we constructed a linear regression of plot average age
against distance to seed source.
Microsites
We related the density of regeneration to pre- and
post-fire basal area by identifying the types of fire
effects on each tree. The categories were live trees
(survivors) dead trees (killed by fire), and post-fire
trees (survivors plus newly established trees). We
then calculated pre-fire live basal area, post-fire live
basal area, and current live basal area for each plot
and then correlated these values with the number of
seedlings and saplings in each plot. The effect of fire
severity on total regeneration in each plot for each
species was identified using ANOVA. Tukey’s HSD
post-hoc test was used to identify differences between
severity types.
Variation in types of ground cover thought to
provide safe microsites for germination was determined by quantifying ground cover characteristics in
four 10 m2 circular subplots in each plot. Subplot
centers were placed equidistant between the plot
center and the plot edge along the four plot radii. In
each subplot the percent cover of logs (C4 cm dbh),
rock ([10 cm across), rock fragments (1–10 cm
across), shrubs, forbs, and grasses were recorded in
one of seven cover classes: 0, absent; 1, \1%; 2,
1–5%; 3, 5–25%; 4, 26–50%; 5, 51–75%; 6,
76–100%). The association between ground cover
characteristics and seedling and sapling abundance
was then identified using a Pearson’s product moment
correlation.
Interannual climate variation
The impact of interannual variation in climate on the
temporal pattern of post-fire regeneration was investigated using correlation analysis. We used climate
data for the period 1962 to 2006 from the Manzanita
Lake, California climate station to represent climate
variation in the study area (WRCC 2010). We used
snowpack depth and water content data from the
lower Lassen snow course for the same period as a
proxy for both the opening of the site in the spring
and also for the availability of groundwater in this
excessively well drained site (CA DWR 2009; USDA
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and down basal area (21.2 m2/ha) with only 3.0 m2/
ha of live basal area. White fir and red fir were
common in the plots but neither species accounted for
[10% of basal area in a plot. Jeffrey pine was present
in a few plots.
Live tree and overall tree density was highest in
the low severity plots. Lodgepole averaged 956 live
stems/ha and 844 down and dead stems/ha in low
severity plots and 216 live and 616 down and dead
stems/ha in the high severity plots (Table 1). White
fir and red fir both had higher densities in high
severity plots than in moderate and low severity plots.
Jeffrey pine densities were overall very low, with
most individuals in high severity plots.
The average size structure of all plots was broadly
similar across severity patches (Fig. 3). The size
structures in the low and moderate severity plots were
nearly identical, but the moderate severity plots had
more large seedlings. Large seedlings were more
abundant than small seedlings in the regeneration
layer in high severity plots. High severity plots also
contained an average of 172 stems ha-1 of fast
growing lodgepole pine in the 5–15 cm diameter
class that established post-fire beginning in 1984. In
general, all plots exhibited size structures dominated
NRCS 2010). We correlated the frequency of establishment dates of seedlings, saplings, and trees with
seasonal and annual average temperature (n = 5
comparisons) and seasonal and annual total precipitation and snowfall (n = 5 comparisons) for the
current year and the previous year. Finally, we
correlated the frequency of establishment dates with
maximum snow water equivalent and snow pack
depth for the current year, previous year, and for
three year averages (n = 12 comparisons). We used a
Bonferroni’s correction to reduce Type I errors in all
cases.
Results
Stand structure
Basal area in all plots was dominated by lodgepole
and ranged from 11.4 m2/ha to 73.9 m2/ha (Table 1).
Low severity plots averaged 45.3 m2/ha of live basal
area and 9.9 m2/ha of dead and down basal area.
Moderate severity plots had roughly equal amounts of
live (21.9 m2 ha-1) and dead and down basal area
(16.7 m2 ha-1). High severity plots were mostly dead
Table 1 Average (±s.e.) of basal area and density (ha-1) by patch severity and tree status (live, snag, or dead and down)
Severity:
Basal Area (m2/ha)
Low
Density (stems/ha)
Moderate
High
Low
Moderate
High
Abco
Live
0.2 ± 0.0
10 ± 0.8
0.4 ± 1.1
44 ± 67
48 ± 111
28 ± 38
Dead & down
0.0 ± 0.2
0.8 ± 2.7
1.6 ± 0.6
4 ± 13
156 ± 130
300 ± 178
Snag
0.0 ± 0.0
0.1 ± 0.3
0.3 ± 1.1
0±0
8 ± 17
4 ± 13
Abma
Live
0.0 ± 0.0
0.5 ± 0.3
1.0 ± 2.7
0±0
56 ± 150
28 ± 53
Dead & down
0.0 ± 0.0
0.1 ± 1.0
2.0 ± 2.1
0±0
24 ± 43
188 ± 261
Snag
0.0 ± 0.0
0.0 ± 0.1
0.0 ± 0.0
0±0
4 ± 13
4 ± 13
3.0 ± 11.6
Pico
Live
956 ± 352
540 ± 240
216 ± 183
9.9 ± 11.0
16.7 ± 9.1
21.2 ± 4.6
844 ± 697
744 ± 444
616 ± 238
Snag
Pije
6.1 ± 4.4
0.9 ± 1.9
0.4 ± 0.7
244 ± 183
28 ± 50
12 ± 19
Live
0.0 ± 0.0
0.0 ± 0.0
0.0 ± 4.2
0±0
4 ± 13
4 ± 13
Dead & Down
45.3 ± 6.9
21.9 ± 6.7
Dead & down
0.0 ± 0.0
0.0 ± 0.0
1.7 ± 0.0
0±0
0±0
20 ± 28
Snag
0.0 ± xx
0.0 ± xx
0.0 ± xx
0±0
0±0
0±0
Values represent average over 10 plots in each severity class. Double x’s (xx) indicate there was not enough data to compute the
statistic. Abbreviations are Abco: A. concolor; Abma A. magnifica; Pico P. contorta; Pije P. jeffreyi
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231
Fig. 3 Size structure for
low-, moderate-, and highseverity patches. Each
graph shows the average
size structure of 10 plots. Xaxis shows the upper limit
of the size classes in
centimeters (cm). Note that
the Y-axis is logarithmic for
all three graphs.
Abbreviations are as in
Table 1
by regeneration, with progressively fewer trees in
larger size classes.
Regeneration
Overall patterns
Total regeneration was most abundant (P = 0.015) in
the moderate severity plots (mean = 4,416 stems ha-1) and lowest in the high severity plots
(mean = 1532 stems ha-1). Lodgepole pine seedlings and saplings dominated the regeneration layer
in moderate severity plots while white fir was most
abundant in low severity plots (Table 2). When all
species were analyzed together, regeneration was
significantly different for all three severity types
(ANOVA, P = 0.015) however, post-hoc tests were
significant only for white fir. Lodgepole pine regeneration was proportionally more abundant in high
severity plots (77.0% of total) compared to a more
even distribution of lodgepole pine and white fir in
the moderate and low severity plots. Moreover, the
proportion of lodgepole pine saplings was higher in
high severity plots (172 stems ha-1; 14.6%) than in
low (28 stems ha-1; 1.8%) and moderate (108 stems
ha-1; 4.0%) severity plots. There were no white fir or
red fir saplings in high severity plots and the few
Jeffrey pine seedlings and saplings were present only
in moderate and high severity plots.
Regeneration age
Counted and adjusted ages of seedlings, saplings, and
small trees were widely dispersed in low-severity
plots, but more narrowly dispersed in both moderateand high-severity plots (Fig. 4). High-severity plots
contained very few individuals that were estimated to
be older than 24 years. Nearly all ([97%) stems in
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Table 2 Average (± s.e.) seedling and sapling density and ages in low, moderate, and high severity patches
Severity:
Age (years)
Density (stems/ha)
Low
Moderate
12.7 ± 8.3
12.1 ± 6.9
High
Low
Moderate
High
8.4 ± 5.6
1,584 ± 1,352
1,296 ± 1,181
140 ± 197
Abco
Small seedling
Large seedling
31.0 ± 6.9
30.4 ± 7.2
27.2 ± 4.1
280 ± 376
80 ± 92
12 ± 26
Sapling
49.2 ± 16.5
44.3 ± xx
xx ± xx
44 ± 44
4 ± 13
0±0
60 ± 93
Abma
Small seedling
16.9 ± 9.7
13.9 ± 9.2
10.4 ± 4.9
76 ± 212
192 ± 365
Large seedling
34.6 ± 16.6
29.7 ± 6.5
xx ± xx
28 ± 75
20 ± 39
0±0
Sapling
51.3 ± xx
44.3 ± xx
xx ± xx
16 ± 51
8 ± 25
0±0
420 ± 576
Pico
Small seedling
9.9 ± 3.5
11.1 ± 3.1
10.9 ± 2.5
1,412 ± 1,755
1,800 ± 1,482
Large seedling
18.3 ± 5.4
17.0 ± 2.3
15.9 ± 2.3
120 ± 217
812 ± 563
588 ± 820
Sapling
16.7 ± 16.0
20.8 ± 3.6
19.2 ± 2.7
28 ± 42
108 ± 152
172 ± 352
Pije
Small seedling
7.1 ± 0.0
9.3 ± 2.1
9.8 ± 2.1
8 ± 25
76 ± 93
68 ± 65
Large seedling
Sapling
xx ± xx
xx ± xx
13.9 ± 5.2
xx ± xx
13.0 ± 2.3
14.0 ± 2.2
0±0
0±0
20 ± 39
0±0
64 ± 125
8 ± 17
Ages were determined from modified whorl counts as described in the ‘‘Methods’’ section. Densities are averaged over 10 plots per
severity patch with standard errors shown. Double x’s (xx) and abbreviations are as in Table 1
Fig. 4 Box and whisker
plot of adjusted ages for all
P. contorta individuals
showing distributions by
size class and by patch fire
severity, either high,
moderate, or low severity.
The heavy line is the
median while the boxes
extend to the first and third
quartiles. The whiskers
extend to the last data point
that is no more than 1.5
times the interquartile range
from the box. Outliers are
shown as open circles.
Vertical dashed line shows
the year of the fire
the high severity plots established post-fire, and
corrected tree, sapling and seedlings ages were
B24 years old as expected but a few older stems
were present (Fig. 5). Ages of seedling and saplings
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in the low severity plots had a wider range, up to
56 years. The moderate and low severity plots
contained a few small diameter stems that possibly
had survived the 1984 Badger fire.
Landscape Ecol (2011) 26:225–237
233
Fig. 5 Bar chart of average
ground cover characteristics
for low-, moderate-, and
high-severity plots. An
asterisk (*) indicates
categories that were
significantly different
(ANOVA, P \ 0.05)
between severity classes
was negatively associated with log (P = 0.007) and
rock fragment (P = 0.044) cover. There was no
association between regeneration and microsite characteristics in either the moderate or high severity plots.
However, in low severity plots, lodgepole pine seedlings and saplings were positively associated with
percent cover of shrubs, forbs, and grasses (results not
shown).
Interannual climate variation
Fig. 6 Scatter plot and regression line of the negative
exponential relationship between total P. contorta regeneration
and distance to the nearest cone-bearing individual by plot
The abundance of lodgepole seedlings was related to
temporal variability in snowpack conditions. The
number of seedlings was negatively correlated with
the 3 year average maximum snow depth (r = -0.59,
P = 0.0027). The density of regeneration, however,
was unrelated to snow water equivalent or seasonal or
total temperature or precipitation.
Spatial patterns of regeneration density
Microsite effects on regeneration
Ground cover of logs and rock fragments differed
(logs: P = 0.029; rock fragments: P = 0.004) among
severity classes. However, there was no difference
between percent cover of rocks, forbs, grasses, or
shrubs. Ground cover of logs and rock fragments was
highest in high severity plots, and decreased as
severity decreased (Fig. 5).
Microsite effects on species’ abundance patterns
were negligible. Across all plots, white fir regeneration
Distance to the nearest cone bearing lodgepole pine
individual was a significant predictor of total regeneration in high severity plots. The negative exponential function used to model the number of seedlings
and saplings yielded a significant relationship with
distance (r2 = 0.53, P = 0.025, Fig. 6). Kuiper’s Test
of Uniformity indicated that the directions to the
nearest cone bearing individual were different from a
uniform distribution of directions (P = 0.038). The
circular correlation test comparing wind directions
123
234
and seed source directions was not significant
(P = 0.992). A linear regression using distance as
the independent variable and average estimated age of
lodgepole pine regeneration was not significant
(P = 0.062).
Discussion
Regeneration success in high severity fire patches is
dependent on propagule availability. High and moderate severity plots were dominated by lodgepole
pine regeneration, while low severity plots had
roughly equal amounts of lodgepole pine and white
fir regeneration. Differences may be explained by
each species’ seed weight, and the proximity to seed
sources. Lodgepole pine seeds are very light, and in
this variety may number up to 258,000/kg (Lotan and
Critchfield 1990) while white fir seeds are heavier,
numbering 19,000–39,000/kg (Laacke 1990). In low
and moderate severity plots, trees that survived the
fire provided an ample seed source for both species,
explaining their relative parity in low severity plots
and the abundance of small white fir seedlings in the
moderate severity plots. In high severity patches
seeds would need to be blown in which might favor
the lighter seeded lodgepole pine given equal
distances to seed-source. A similar effect of seed
weight and seed-source proximity on post-fire regeneration of red fir in Oregon was identified by
Chappell and Agee (1996). Red fir has heavier seeds
than white fir, and in the Oregon study, the number of
red fir seedlings was negatively associated with
factors that would influence propagule availability,
such as distance to nearest patch capable of propagule
production, patch size, and percent mortality of
conspecific basal area from fire (Chappell and Agee
1996). Moreover, red fir seedling density was positively related to live residual conspecific basal area
(Chappell and Agee 1996). Each of these effects,
though not all tested here, are analogous for white fir
in the current study.
Interannual variation in successful establishment
by lodgepole pine was correlated with antecedent
weather conditions during key stages in this species’
regeneration cycle. Sierra lodgepole pine cones
mature, open, and release seeds in the fall and then
germinate in the spring (Lotan and Critchfield 1990).
These seeds then overwinter under the snow, and
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Landscape Ecol (2011) 26:225–237
germination begins soon after snowmelt, but as late
as the first day of summer in this location (Lotan and
Critchfield 1990). Our results also indicate that latelying snowpack, here analyzed as annual maximum
snowpack depth, has a strong negative effect on
current year seedling establishment. Mountain hemlock (T. mertensiansa) regeneration in LAVO is also
known to be negatively impacted by deep, late-lying
snow (Taylor 1995). There was a weak but consistently negative correlation between winter, spring,
and summer temperatures and current year snowpack
(results not shown) and no relationship between
current year temperatures and regeneration density.
Thus it seems that late-lying snowpack inhibits
germination in the current year. However, the relationship between current year temperatures and
snowpack perhaps indicates that current year temperatures are less important to germination and that
snowpack is a limiting factor in the late spring.
Microsite influences on establishment have been
demonstrated for a number of tree species in the
Pacific Northwest. Perhaps most influential is moisture stress, which has been shown to significantly
alter red fir regeneration and survival (Selter et al.
1986; Chappell and Agee 1996). In western hemlockSitka spruce (Tsuga heterophylla-Picea sitchensis)
forests, nurse logs are critically important substrates
promoting establishment (Harmon and Franklin
1989). In an experimental regeneration study of
ponderosa pine in central Oregon using ponderosa
pine seeds, seedlings germinated better when buried
and shaded to simulate rodent caches (Keyes et al.
2009). In our study, measured variation in microsites
had little to no effect on establishment of lodgepole
pine in high severity patches but there was a negative
effect of logs and rock fragments on white fir.
However, lodgepole pine seedlings were positively
related to cover of shrubs, grasses, and forbs in low
severity plots. Yet these types of cover tended to be
higher in high severity plots, and this relationship was
only discovered in our post-hoc analysis. The negative effects of logs and rocks on white fir regeneration
could be artifacts of the fact that these types of cover
were higher in high severity plots. Here white fir
seedlings would be subject to increased moisture
stress, akin to the effect of moisture stress on red fir
regeneration (Chappell and Agee 1996).
Disturbance intensity can influence plant regeneration through its modification of the post-disturbance
Landscape Ecol (2011) 26:225–237
environment, most directly through plant and propagule mortality (Halpern and Franklin 1990), but also
through modification of abiotic conditions (Chappell
and Agee 1996). The highest abundance of lodgepole
pine regeneration and the highest total amount of
regeneration was in the moderate severity plots. This
suggests that moderate levels of disturbance promote
the optimal conditions for the emergence and establishment of the two dominant species in this system.
These patches, with some areas of full sun and some
shaded pockets, as well as their abundant local seed
sources, would promote both lodgepole pine regeneration on mineral soil in full sun (Lotan and
Critchfield 1990), and white fir regeneration on
mineral soil in partial shade (Laacke 1990). In
contrast, severely burned patches, with no canopies
and higher moisture stress, tend to favor lodgepole
pine. The abiotic conditions across the majority of
the severely burned areas are harsh enough to
preclude establishment by all species except lodgepole pine which is noted for its wide ecological
amplitude (Franklin and Dyrness 1988). The lodgepole pine stand we investigated occupies a pumice
flat characterized by cold air drainage (Franklin and
Dyrness 1988), short frost-free periods (USDANRCS 2010), and soils that are very well drained,
with extremely limited water holding capacity
(USDA-NRCS 2010). The timing of high severity
patch regeneration is thus limited by seed source
proximity and the composition of regeneration is
limited by abiotic conditions.
The empirical relationship demonstrated here
between distance and regeneration abundance illustrates a strong spatial influence on patch infilling in
this system. We determined the ages of over 1,200
seedlings and saplings, and greater than 98% of stems
in the high and moderate fire severity plots were
B24 years old—a pattern consistent with post-fire
establishment following the 1984 fire. Seedlings and
saplings that survived the fire in high severity patches
were found in small unburned areas skipped by the
fire similar to surviving Rocky Mountain lodgepole
pine in the 1988 Yellowstone fires (Turner et al.
1997; Nyland 1998). The distribution of ages of
seedlings and saplings was not uniform, however. A
post-fire peak of regeneration centered around the 15year age class is notably evident. Following this age
class, counted individuals decrease towards the
present; however, yearly counts were never \60%
235
of the maximum number. Interannual variation in
maximum snowpack depth indicates that lodgepole
pine regeneration is negatively impacted by late-lying
snow. Because all years had a large number of
regenerating individuals, we posit that seasonal
climatic conditions only mediate regeneration and
are not limiting. While some years may be more
favorable for regeneration than others, no single year
can be identified that was particularly favorable or
unfavorable. In contrast, the peaks of regeneration
found by Chappell and Agee (1996) were considerably narrower, occurred in a 3–5 year window
following their studied fires, and were hypothesized
to coincide with periodic peaks in red fir cone
production. Since lodgepole pine produces seed
annually, and climate was not a factor, we hypothesize that this pulse represents some kind of distance
delay followed by the sustained influence of wind
speed and direction on regeneration density.
Nyland’s (1998) work on Rocky Mountain lodgepole pine stand development patterns hypothesizes
different pathways depending on the overall level of
serotiny within the stand. The Converging Tree
Island posits that widely spaced legacy lodgepole
pine slowly create expanding islands of regeneration
which over time merge to form a closed, multi-aged
canopy (Nyland 1998). The statistical work presented
here supports the idea that Sierran lodgepole, with no
evidence of serotiny, follows the Converging Tree
Island Pathway (Nyland 1998). Our study presented
empirical evidence of this Pathway by establishing a
strong relationship between the total number of
regenerating stems and the distance and direction to
the nearest cone bearing Sierran lodgepole pine
individual. The relationship between the amount of
regeneration and the distance to the nearest cone
bearing individual strongly followed the negative
exponential dispersal kernel that has been proposed
by a number of authors (Willson 1992; Borchert et al.
2003; Greene et al. 2004). This relationship, while
strong at first, may break down over time as seedlings
mature and begin to produce their own cones. In
Badger Flat, 11 cone-bearing trees had established
after the 1984 burn and they had an average age
23 years. If lodgepole pine had serotinous cones in
this study area, post-fire regeneration would have
been expected to be greatest in the high severity
plots, as was found in the post-fire period in
Yellowstone National Park (Turner et al. 1997).
123
236
Our stands exhibited no relationship between pre-fire
live basal area and the total number of regenerating
individuals. Our estimate of pre-fire live basal area
for all plots is similar to live basal area of unburned
stands (P = 0.055, t-test) in nearby unburned lodgepole pine stands (Taylor 2000).
Because the direction to the cone bearing individual was different than expected at random and
because the dominant direction of seed source was
not different from the dominant wind direction, we
hypothesize that wind and not rodents are the
primary dispersal vector for lodgepole pine in
LVNP. Rodents prefer to cache larger seeds, especially the large seeds of Jeffrey, ponderosa, and
sugar pine and prefer to consume lodgepole pine
seeds immediately (Vander Wall 2008). In our
system, the large seeded red and white firs probably
complement the supply of Jeffrey pine seeds available to rodents for caching. The small seeded
lodgepole pine, however, is very rarely cached and
rarely germinates when cached (Vander Wall 2008).
In contrast, Jeffrey pine seeds are very often cached,
and regenerate at much higher rates when cached
(Vander Wall 2008). Thus, we hypothesize that wind
dispersal of lodgepole pine seeds is the dominant
mechanism of propagule availability into the area of
the Badger Fire.
The relatively slow rate of infilling of lodgepole
pine regeneration after the Badger Fire in the high
severity patches raises questions about the use of
static age structures to identify historic fire severity
patterns. While Johnson et al. (1994) examined
problems with static age structure interpretation from
an aspatial point of view, our data suggest that spatial
variability in regeneration abundance and timing
itself can lead to false interpretations regarding
disturbance dynamics that shape the static age
structure of lodgepole pine forests. Since patch size
and shape influence the tree age distribution, inferences about fire severity and regeneration dynamics
may be complicated. Since the interior of a patch fills
later than the edges, aggregating plot level age
structures may indicate more than one regeneration
pulse, or may reveal an age structure that is typical
for a continuously regenerating forest. This could
lead to the erroneous conclusion that tree fall gap
dynamics or low or moderate severity fires are the
predominant disturbances in the ecosystem when it
may be high severity fire.
123
Landscape Ecol (2011) 26:225–237
Acknowledgments A. Hurley, T. Korkmaz, and E. Lawley
assisted with the collection of field data. T. Garcia and T.
Rickman provided invaluable logistic support. This research
was conducted with financial assistance from and under
agreement with the National Park Service through study
number LAVO-00812. The first author also received a
Pennsylvania State University, Department of Geography
Academic Enrichment Award. We also thank the editorial
staff and two anonymous reviewers.
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