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Patterns in whitebark pine regeneration and their relationships to biophysical site characteristics in southwest Montana, central Idaho, and Oregon, USA

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Declines of whitebark pine (Pinus albicaulis Engelm.) have occurred across much of the species' range over the last 40 years due to mountain pine beetle outbreaks and white pine blister rust infection. Management efforts to stem these declines are increasing, yet the long-term success of whitebark pine depends on the species itself adapting to the modern environment. Natural regeneration will be a critical part of this process. We examined patterns in natural whitebark pine regeneration as related to the biophysical environment in sixty 0.1 ha plots in Montana, Idaho, and Oregon. Whitebark pine regeneration was present in 97% of our plots and varied widely in density from 0 to 17 000 seedlings/ha and 0 to 2680 saplings/ha. Using nonparametric correlation analysis and ordination techniques, we found whitebark pine regeneration abundance was unrelated to stand age but significantly related to several biophysical site characteristics, including positive relationships with elevation and canopy tree mortality caused by mountain pine beetle and negative relationships with moisture availability, temperature, and subalpine fir importance. Our findings indicate that whitebark pine is regenerating in many areas and that the widespread mortality from recent mountain pine beetle outbreaks may provide suitable settings for whitebark pine regeneration given sufficient seed sources.
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Patterns in whitebark pine regeneration and their
relationships to biophysical site characteristics in
southwest Montana, central Idaho, and Oregon,
USA
Evan R. Larson and Kurt F. Kipfmueller
Abstract: Declines of whitebark pine (Pinus albicaulis Engelm.) have occurred across much of the species’ range over the
last 40 years due to mountain pine beetle outbreaks and white pine blister rust infection. Management efforts to stem these
declines are increasing, yet the long-term success of whitebark pine depends on the species itself adapting to the modern
environment. Natural regeneration will be a critical part of this process. We examined patterns in natural whitebark pine
regeneration as related to the biophysical environment in sixty 0.1 ha plots in Montana, Idaho, and Oregon. Whitebark
pine regeneration was present in 97% of our plots and varied widely in density from 0 to 17 000 seedlings/ha and 0 to
2680 saplings/ha. Using nonparametric correlation analysis and ordination techniques, we found whitebark pine regenera-
tion abundance was unrelated to stand age but significantly related to several biophysical site characteristics, including
positive relationships with elevation and canopy tree mortality caused by mountain pine beetle and negative relationships
with moisture availability, temperature, and subalpine fir importance. Our findings indicate that whitebark pine is regener-
ating in many areas and that the widespread mortality from recent mountain pine beetle outbreaks may provide suitable
settings for whitebark pine regeneration given sufficient seed sources.
Re
´sume
´:Des de
´clins du pin a
`e
´corce blanche (Pinus albicaulis Engelm.) sont survenus dans presque toute son aire de re
´-
partition au cours des 40 dernie
`res anne
´es a
`cause des infestations du dendroctone du pin ponderosa et des infections de la
rouille ve
´siculeuse du pin blanc. Les efforts d’ame
´nagement pour enrayer ces de
´clins augmentent, mais a
`long terme, le
succe
`s du pin a
`e
´corce blanche de
´pend de son adaptation a
`l’environnement moderne. La re
´ge
´ne
´ration naturelle sera un
e
´le
´ment crucial de ce processus. Nous avons e
´tudie
´les patrons de la re
´ge
´ne
´ration naturelle du pin a
`e
´corce blanche en
fonction de l’environnement biophysique dans 60 placettes de 0,1 ha dans les e
´tats du Montana, de l’Idaho et de l’Oregon,
aux E
´tats-Unis. La re
´ge
´ne
´ration du pin a
`e
´corce blanche e
´tait pre
´sente dans 97 % des placettes et sa densite
´variait e
´nor-
me
´ment, soit de 0 a
`17 000 semis/ha et de 0 a
`2680 gaules/ha. En utilisant des techniques d’analyse de corre
´lation non pa-
rame
´trique et d’ordination, nous avons e
´tabli que l’abondance de la re
´ge
´ne
´ration de pin a
`e
´corce blanche n’e
´tait pas relie
´e
a
`l’a
ˆge du peuplement, mais qu’elle e
´tait relie
´ea
`plusieurs caracte
´ristiques biophysiques de la station, incluant des rela-
tions positives avec l’altitude et avec la mortalite
´des arbres dominants cause
´e par le dendroctone du pin ponderosa et des
relations ne
´gatives avec la disponibilite
´en eau, la tempe
´rature et l’abondance du sapin subalpin. Nos re
´sultats indiquent
que le pin a
`e
´corce blanche se re
´ge
´ne
`re a
`plusieurs endroits et que la forte mortalite
´cause
´e par les re
´centes infestations du
dendroctone du pin ponderosa peut cre
´er des conditions ade
´quates pour l’e
´tablissement de sa re
´ge
´ne
´ration si les sources de
semences sont suffisantes.
[Traduit par la Re
´daction]
Introduction
The continued persistence of whitebark pine (Pinus albi-
caulis Engelm.) as an important species in high-elevation
forests of western North America is a topic of major con-
cern among land managers and researchers (Tomback et al.
2001b). Dramatic declines have been observed in the health
and dominance of whitebark pine across the species’ range
over the last 40 years (Kendall and Keane 2001). These de-
clines have been attributed to the invasive white pine blister
rust (Cronartium ribicola (A. Dietr.) J.C. Fisch.), advancing
succession as a result of fire suppression, and episodic
mountain pine beetle (Dendroctonus ponderosae Hopkins)
outbreaks over the 20th century. Concern over the deteriora-
tion of whitebark pine forests is based on the potential cas-
cade of ecological effects that may result because of the
critical role the species fills in subalpine forest communities
through enhanced biodiversity; through regulation of hydrol-
ogy and watershed dynamics; and as the foundation of an
ecosystem involving Clark’s nutcrackers (Nucifraga colum-
biana Wilson), red squirrels (Tamiasciurus hudsonicus
Received 21 July 2009. Accepted 22 January 2010. Published on
the NRC Research Press Web site at cjfr.nrc.ca on 26 February
2010.
E.R. Larson1,2 and K.F. Kipfmueller. Minnesota
Dendroecology Laboratory, Department of Geography,
University of Minnesota – Twin Cities, 414 Social Sciences
Tower, 267 – 19th Avenue South, Minneapolis, MN 55455,
USA.
1Corresponding author (e-mail: larsonev@uwplatt.edu).
2Present address: Department of Social Sciences/Geography,
University of Wisconsin – Platteville, 1 University Plaza, 244
Gardner Hall, Platteville, WI 53818, USA.
476
Can. J. For. Res. 40: 476–487 (2010) doi:10.1139/X10-005 Published by NRC Research Press
Trouessart), grizzly bears (Ursus arctos L.), and black bears
(Ursus americanus Pallas) (Ellison et al. 2005).
In response to these declines, active management and re-
storation projects in whitebark pine forest are becoming in-
creasingly common, yet to persist over the long term the
trees themselves must adapt to changes in the biotic and
abiotic environment, particularly with respect to blister rust.
Change and adaptation in species and natural systems occurs
through selective processes that operate at the scale of gen-
erations, and therefore successful whitebark pine regenera-
tion will be one critical component of the long-term success
of this species.
Early research on whitebark pine regeneration focused
primarily on the mutualistic relationship between whitebark
pine and its primary dispersal agent, the Clark’s nutcracker,
and on the ecological and evolutionary implications of this
relationship, particularly with respect to the behavioral ten-
dencies of Clark’s nutcrackers when they create seed caches
(Lanner 1982; Tomback 1982). Clark’s nutcrackers prefer-
entially cache whitebark pine seeds in open and recently dis-
turbed settings, and most studies of the patterns and
abundances of whitebark pine regeneration have focused on
postfire settings (e.g., Tomback et al. 1993, 1995, 2001a).
Clark’s nutcrackers have also been documented caching
whitebark pine seeds in a variety of other microsites
(Hutchins and Lanner 1982), and recent research identified
variable levels of advanced whitebark pine regeneration
across a wide spectrum of biophysical settings, including
stands that had experienced high levels of mortality related
to 20th century mountain pine beetle outbreaks (Mellmann-
Brown 2005; Moody 2006).
The community dynamics and spatial patterns of animal-
dispersed plants are highly influenced by the nonrandom be-
haviors of their dispersalists (Jordano et al. 2007), yet few
assessments of patterns in whitebark pine regeneration at
the landscape-scale have been conducted (but see Zeglen
2002). A more complete understanding of where whitebark
pine regeneration is likely to occur and succeed would en-
hance management and restoration activities in whitebark
pine communities, particularly with respect to site selection
for the outplanting of blister-rust-resistant whitebark pine
seedlings (Hoff et al. 2001) and the application of prescribed
fire (Keane and Arno 2001). In response to this need, our
study seeks a better understanding of the spatial patterns in
natural whitebark pine regeneration and how these patterns
relate to the biophysical environment. Our guiding questions
for this research were (1) Is whitebark pine regenerating in
our study area?, (2) How do patterns of whitebark pine re-
generation vary across the landscape and does this variabil-
ity relate to the biophysical environment?, and (3) How do
patterns of whitebark pine regeneration relate to past distur-
bances and in particular mountain pine beetle outbreaks?
Study area
Whitebark pine is widely distributed across the western
United States, with the native range of the species spanning
368–558N and 1088–1278W. Within this range, whitebark
pine habitat is found from the lower subalpine zone to the
upper forest limits and timberline (Arno and Hoff 1990).
Our study area extends from southwest Montana to western
Oregon between ca. 428and 458N, with study sites in the
Gravelly Range and Pioneer Mountains of Montana, the Sal-
mon River Mountains of Idaho, and the Wallowa Moun-
tains, Paulina Peak, and Cascade Range of Oregon (Fig. 1).
These mountain ranges are located within the Beaverhead–
Deerlodge National Forest, the Payette National Forest, the
Wallowa–Whitman National Forest, and the Deschutes Na-
tional Forest, respectively.
Topographic diversity in mountain environments strongly
influences ecological patterns and processes. The diverse
character of the different mountain ranges included in our
study area provided us with a picture of whitebark pine re-
generation across a broad array of physical settings. The
Gravelly Range contains some steep and rugged slopes, but
our study sites were located on the broad crest of the range
that exists predominantly above 2900 m and has generally
rolling topography with gentle slopes. In contrast, the Pioneer
Mountains, Salmon River Mountains, and Wallowa Moun-
tains are each an extensive mountain massif and highly dis-
sected by glacial valleys and ridges, and our study sites were
situated in areas of steep slopes and sharp environmental gra-
dients. Our sites in the Cascades were located on the south
and southwest flanks of Mount Bachelor, a relatively young
volcanic mountain with a regular conical shape, and at the
crest of Black Crater, an irregularly shaped cinder cone. Pau-
lina Peak is the remnant of Newberry Volcano, and our sites
were situated along a high-elevation rim bordering the south
and east sides of what is now Newberry Caldera.
Broad similarities and a few distinct differences existed in
the annual patterns of temperature and precipitation at our
sites based on site-specific climate data obtained from the
PRISM data set (PRISM Group, Oregon State University,
http://www.prismclimate.org, created 13 Nov 2008) (Daly et
al. 2008). In general, the sites shared a common pattern of
drier summers and wetter winters, although the peak in win-
ter precipitation was much more pronounced in the Cas-
cades, Wallowa Mountains, and Salmon River Mountains
than at the other sites (Fig. 1). Mean total annual precipita-
tion of the different mountain ranges was affected by re-
gional-scale rain shadows and ranged from 783 mm across
the sites on Paulina Peak up to 2000 mm at the Cascades
sites, whereas mean monthly maximum and minimum tem-
peratures exhibited a gradient in extremes from the western,
maritime sites to the eastern, continental sites (Fig. 1). Vari-
ability in the climate conditions within each landscape was
highly influenced by the general topography of the mountain
ranges, with more variable topography and climate in the
Pioneer Mountains, Salmon River Mountains, and Wallowa
Mountains contrasting with less variability in the Gravelly
Range, Paulina Peak, and the Cascades (Fig. 1).
Our study sites were located in the upper forest zones of
each mountain range where whitebark pine was the dominant
or codominant tree species (Table 1). In addition to white-
bark pine, several other tree species occurred in at least one
site, including subalpine fir (Abies lasiocarpa (Hook.) Nutt.),
Engelmann spruce (Picea engelmannii Parry ex Engelm.),
lodgepole pine (Pinus contorta Douglas ex Louden), Doug-
las-fir (Pseudotsuga menziesii (Mirb.) Franco), and mountain
hemlock (Tsuga mertensiana (Bong.) Carr.). Herbaceous
communities varied considerably among the mountain ranges
and among the individual sites within each range because of
Larson and Kipfmueller 477
Published by NRC Research Press
differences in the slope, aspect, substrate, and topographic
position of each site. The dominant species based on percent-
age of ground cover included Arnica alpine (L.) Olin, Juni-
perus spp., Lupinus spp., Penstemon spp., Phlox hoodii,
Ribes spp., Phyllodoce empetriformis (Sm.) D. Don, Vacci-
nium scoparium Leiberg ex Coville, and Salix spp.
Methods
Data collection and processing
We used a geographic information system to identify the
geographic centroid of 60 upper-elevation stands among the
different mountain ranges that contained whitebark pine
based on geospatial USDA Forest Service stand inventory
data provided by each National Forest. We viewed aerial
photographs to confirm the vegetation type at each plot.
These stands existed on a variety of slopes and aspects and
were near the tree line, yet still appeared to have relatively
continuous canopies. The Universal Transverse Mercator co-
ordinates of each stand centroid were marked on field maps
and programmed into a handheld global positioning system
device.
Fig. 1. Study area showing the range of whitebark pine (gray shading), location of studied mountain ranges (black dots), and climographs
for each mountain range. The climographs represent the mean monthly maximum, mean monthly minimum, and mean monthly precipitation
for each plot as scatter points with the overall means of each of these variables for each mountain range indicated by the line graphs (tem-
perature) and the bar graphs (precipitation). The data were derived from PRISM climate grids for the United States (PRISM Group, Oregon
State University, http://www.prismclimate.org, created 13 Nov 2008) (Daly et al. 2008).
478 Can. J. For. Res. Vol. 40, 2010
Published by NRC Research Press
In the field, we found that two of the stand centroids were
located on cliff edges or other unsafe slopes, four were in
forest openings, one was approximately 25 m offshore in a
lake, and one was on the margins of a treeless wetland. In
these cases, we adjusted the plot location 100 m in a ran-
domly chosen direction. In addition, two of the larger stands
in the Wallowa Mountains appeared relatively heterogene-
ous in disturbance history, structure, and composition. We
therefore used aerial photographs, stand inventory maps,
and the global positioning system device to randomly select
up to two additional sites within these stand boundaries.
A 0.1 ha circular plot was placed at the centroid or ad-
justed centroid of each stand to collect site characteristic
and forest demographic information. We recorded the eleva-
tion, average slope, aspect, topographic position, microsite
characteristics, and substrate type for each plot. The species,
diameter at breast height, canopy class, and health of all
trees were recorded within the 0.1 ha plot. Canopy class
was defined as canopy (50% of the tree canopy exposed to
direct overhead light) and subcanopy (<50% of the tree can-
opy exposed to overhead light). Tree health was subjectively
categorized as alive (healthy canopy, fully capable of repro-
duction), declining (partial canopy dieback but still capable
of producing cones, or the presence of pitch tubes caused
by active mountain pine beetle infestation), and dead. All
living whitebark pine trees were visually searched for evi-
dence of blister rust infection, including active cankers, in-
active cankers, rodent chew, and flagging branches. We did
not survey dead whitebark pine trees for blister rust because
of the tendency of most dead trees in our plots to have lost
their small branches and sloughed off their bark, greatly re-
ducing our ability to identify past infections. All dead trees
were inspected for physical damage, char, and j-shaped
mountain pine beetle galleries to determine the cause of
death.
We tallied all saplings (2 cm diameter at ground level
and <5 cm diameter at breast height) by species and all
seedlings (<2 cm diameter at ground level) by species
within nested plots of 0.05 and 0.01 ha, respectively. Incre-
ment cores were collected along two radii as low on the bole
as possible from all living and dead trees 5 cm diameter at
breast height within the 0.05 ha plot to determine stand age
and disturbance history and to detect the presence of blue
stain fungus, an indicator of mortality caused by mountain
pine beetle. Additional cores were taken through the scar
face and healing lobes of any trees in the coring plot that
displayed basal or strip-kill scars to date the event that
caused the scar.
All of the increment cores were air-dried, glued into core
mounts, and sanded using progressively finer grit sand paper
until individual xylem cells were clearly visible under 7–
45magnification. We crossdated each core with master
chronologies developed for each mountain range using vis-
ual and graphical methods (Stokes and Smiley 1996). The
inner dates of cores that did not reach the pith of a tree but
exhibited sufficient curvature in the inner rings were cor-
rected using pith estimators based on concentric circles and
constant growth rates. Cores that were rotten near the center
and did not contain pith or sufficient curvature to estimate
the rings to pith were assigned minimum ages and excluded
from our age-structure analyses. Cores taken from scarred
trees were examined in the context of multiple lines of evi-
dence, including field notes on the presence or absence of
charcoal, stand structure data, timing of other injuries in the
same plot, and presence or absence of blue stain at the scar
face, to assign a cause to the injury (physical abrasion,
mountain pine beetle strip kill, fire, or unknown disturb-
ance).
We summarized the age-structure data into 10 year age
classes and calculated a number of disturbance-related met-
rics. Minimum stand age was determined as the age of the
oldest tree in the plot and was used as a measure of the
time since the last stand-replacing disturbance. We identi-
fied cohorts where the sum of trees that established over
any 30 year period (three consecutive age-structure bins)
was 5 trees and 25% of the total number of cored trees
in the plot and used the time since the last cohort establish-
ment as an estimate of the time since the last disturbance,
stand replacing or not. We assigned cohort establishment
dates, fire scar dates, and mortality events related to moun-
tain pine beetle to decadal bins and used these to calculate a
decadal disturbance frequency for each plot.
We collected site-specific climate data for each of our
plots. The climate data we used were sampled from the
Spline climate data set developed by Rehfeldt (2006) and
from the PRISM climate data developed by the PRISM
Group at Oregon State University (Daly et al. 2008). The
climate variables we obtained included mean monthly maxi-
mum and minimum temperatures and mean monthly precip-
itation from the PRISM data, and mean annual precipitation
and mean annual temperature from the Spline data set. We
seasonalized the monthly variables into spring (MAM),
summer (JJA), fall (SON), and winter (DJF) variables and
included a number of derived variables related to the length
of the growing season and the number of degree-days
(Table 2). Following Rehfeldt et al. (2008), we also calcu-
Table 1. Site setting, stand structure, and stand compositional information for each mountain range.
Importance values
Range n
Elevation
(m)
Density
(trees/ha)
Basal area
(m2/ha)
Pinus
albicaulis
Abies
lasiocarpa
Picea
engelmannii
Pinus
contorta
Tsuga
mertensiana
Cascades 6 2330±41 802±130 31±4 179±6 6±4 0±0 0±0 14±7
Gravelly Range 8 2887±27 848±120 34±4 176±12 22±11 2±1 0±0 0±0
Paulina Peak 7 2306±29 976±165 36±5 112±20 0±0 0±0 74±21 13±6
Pioneer Mountains 14 2728±27 1051±177 38±5 152±12 2±1 9±5 31±12 0±0
Salmon River Mountains 12 2369±26 378±38 30±4 112±13 74±11 2±1 11±7 0±0
Wallowa Mountains 13 2348±35 519±45 25±3 92±14 73±10 4±2 31±15 0±0
Note: Values are means ± 1 SD.
Larson and Kipfmueller 479
Published by NRC Research Press
lated a growing season dryness index as the ratio of total
summer precipitation to the degree-days >5 C8that accumu-
late during the frost-free season based on the Spline data
(Table 2). Lower values of the growing season dryness in-
dex indicate sites that are more likely to experience drought
conditions over the course of a year.
We calculated a suite of standard forest metrics (fre-
quency, relative frequency, basal area, relative basal area,
and importance values) for each species present and strati-
fied by canopy class and health category (Table 2). In addi-
tion to the raw variables of slope, aspect, and elevation, we
converted plot aspect to a linear metric, calculated relative
elevation, and determined a topographic relative moisture
index (TRMI) and a relative TRMI for each plot. Linear as-
pect was calculated as 1 + cos[p(aspect – 45)/180] and re-
sulted in a value from 0 (warmer, drier southwest-facing
slopes) to 2 (cooler, moister northeast-facing slopes). Rela-
tive elevation was calculated by subtracting the elevation of
the lowest plot within a mountain range from the elevation
of each of the other plots and represented an estimation of
the elevational position of each stand within the distribution
of sampled whitebark pine stands in each of the mountain
ranges. The TRMI was developed to quantify the effects of
stand-scale topography on effective moisture availability in
mountainous landscapes (Parker 1982). TRMI values range
from 0 to 60 and were calculated as the sum of values as-
signed to slope steepness (0–10), slope configuration (0–
10), slope aspect (0–20), and slope position (0–20). Lower
numbers indicate sites with less moisture availability and
higher numbers indicate sites with greater moisture avail-
ability. To enhance our abilities to use the TRMI in compar-
isons among mountain ranges, we calculated a rTRMI for
each site as follows:
½1rTRMIs¼TRMIsMAPs
1
nX
n
i¼n
TRMIi
where TRMIsand MAPsare the TRMI and mean annual
precipitation (PRISM data) for site s, respectively, and
TRMIiis the TRMI for the ith site. This measure incorpo-
rates site-specific precipitation and topography to produce a
measure of effective moisture availability that is comparable
across sites with similar topography but different climate re-
gimes.
Data analysis
We used two nonparametric tests and ordination analyses
to explore the potential relationships between whitebark pine
regeneration and site biophysical characteristics across our
study area. We used Kruskal–Wallis’ one-way analysis of
variance by ranks to assess the overall similarity in levels
of whitebark pine regeneration among the different moun-
tain ranges and Kendall’s tcorrelation analyses to describe
the strength of the relationships among individual biophysi-
cal site characteristics and whitebark pine regeneration.
We used both unconstrained (Principal Coordinates Anal-
ysis; PCO) and constrained (Canonical Correlation Analysis;
CCorA) ordinations to address the multicollinearity in our
environmental variables and to further assess the relation-
ships identified in our correlation analyses. Because of the
similarity in the results of our Kendall’s tcorrelation analy-
ses comparing seedling and sapling densities to biophysical
site characteristics, we used only the variables identified as
significant with respect to sapling density to create a matrix
Xthat we ordinated using Canonical Analysis of Principal
Coordinates (CAP). CAP is conducted by first using PCO
on any type of dissimilarity matrix or distance measure, and
then conducting CCorA on the axes of the PCO (Anderson
and Willis 2003). This approach allows for flexibility in the
choice of dissimilarity or distance measures, and by con-
ducting the CCorA on the PCO axes produces less arbitrary
results for the CCorA. Using this approach, CAP has been
shown to be effective in identifying ecological patterns in
multivariate data that are otherwise masked in the results of
unconstrained ordinations (Anderson and Willis 2003). Ma-
trix Yfor the CCorA was composed of whitebark pine seed-
ling and sapling densities. Our ordinations were based on a
symmetrical Gower dissimilarity matrix due to the different
Table 2. Biophysical variables calculated for each site including
derived climate variables and stand and site metrics calculated
for each site.
Code Description
Derived climate variable
D100 Day of year the sum of degree-days reaches 100
DD0 Degree-days <0 8C
DD5 Degree-days >0 8C
FFP Day of year of the first freezing date of autumn
FDAY Length of the frost-free period
GSDD5 Degree-days >5 8C accumulating in the frost-free
period
GSP Growing season precipitation (April to September)
MMAX Mean maximum temperature in the warmest month
MMIN Mean minimum temperature in the coldest month
MTCM Mean temperature in the coldest month
MTWM Mean temperature in the warmest month
SDAY Day of year of the last freezing date of spring
ADI Annual dryness index (DD5/MAP)
SMI Summer dryness index (GSDD5/MAP)
GDI Growing season dryness index (GSP/DD5)
Calculated stand metric
Freq Frequencya
RF Relative frequencya
BA Basal area (m2)a
rBA Relative basal areaa
IV Importance values ([RF + rBA]100)a
lASP Linear aspect (Cosine[Aspect+45])
Elev Elevation
rElev Relative elevation (see text for definition)
TRMI Topographic relative moisture index
rTRMI Relative topographic relative moisture index (see
text and eq. 1 for definition)
Min Age Minimum age of stand
DDF Decadal disturbance frequency
TSC Time since cohort establishment
Note: MAP, mean annual precipitation.
aCalculated for each permutation of species present, canopy class (C =
canopy, S = subcanopy), and health category (A = alive, DEC = declining,
D = dead).
480 Can. J. For. Res. Vol. 40, 2010
Published by NRC Research Press
states of the biophysical variables. All ordinations were con-
ducted using the program CAP v. 12 (Anderson and Willis
2003), with the program determining the number of PCO
axes (m) to include in the canonical analysis by sequentially
increasing the number of mand each time calculating the re-
sidual error. The number of axes resulting in the minimum
residual error is chosen, with the test run on 9999 random
permutations.
Results
We inventoried 1240 living seedlings, 3051 living sap-
lings, and 4176 trees, of which we cored 2346, in 60 plots
during the summers of 2006–2008 (Table 3). Of these,
1004, 1546, and 2666 were whitebark pine, respectively.
We observed whitebark pine regeneration in 97% (n=58)
of our plots, with seedling densities ranging from 0 to
17 000/ha and sapling densities ranging from 0 to 2680/ha
(Table 3). Increment cores were collected along two radii
from 2346 trees, and we were able to assign accurate inner
dates or pith estimations to 87% (n=2046) of the cored
trees. The majority of the undated cores were collected
from trees with rotten centers. Pith was included in 16%
(n=365) of the cores and the average correction for cores
that did not include pith was 7 ± 5 SD years (range: 1–
30 years). Stand setting, structure, and composition varied
widely among the mountain ranges (Tables 1 and 3). Over-
all, blister rust infections were observed on 37% (n=660)
of the living whitebark pine trees we inventoried, with rates
of infection in individual plots ranging from 0% to 100%.
Out of the 2666 whitebark pine trees inventoried, 33% (n=
887) were dead. Mountain pine beetle activity was the pri-
mary cause of mortality, with 83% (n=619) of all dead
whitebark pine exhibiting extensive pitch tubes, beetle gal-
leries, and (or) blue stain fungus. We found evidence of
past fires in 35% (n=21) of our plots in the form of fire-
scarred trees and (or) postfire cohorts. In general, disturb-
ance frequency was highest in the Salmon River Mountains
and lowest in the Wallowa Mountains (Table 3).
Whitebark pine seedling and sapling abundances varied
significantly among the six mountain ranges (seedlings: H=
33.29, P< 0.001; saplings: H= 33.66, P< 0.001) (Table 4).
Our correlation analyses identified a number of significant
relationships between biophysical site characteristics and
both seedling and sapling abundance (Table 5). The stron-
gest relationship for both categories of regeneration was an
inverse relationship with the importance of subalpine fir.
Both seedlings and saplings were positively correlated with
the density of whitebark pine as well as the density of dead
trees and whitebark pine killed by mountain pine beetle.
Whitebark pine regeneration was positively correlated with
overall stand density and the density of lodgepole pine and
mountain hemlock. Elevation and whitebark pine regenera-
tion was positively correlated, with relative elevation show-
ing a stronger relationship than absolute elevation. Several
climate variables were significantly related to both seedling
and sapling abundance (Table 5), illustrating the general pat-
tern of greater whitebark pine regeneration at the cooler,
drier sites of our study area. The direction of these relation-
ships was similar between seedlings and saplings, but the
strength of the relationships was greater with respect to sap-
ling abundance in almost all cases. Whitebark pine sapling
density was also weakly but significantly related to the dis-
turbance frequency of our sites.
The CAP results refined the patterns we identified in our
correlation analyses. The first two axes of the unconstrained
PCO ordination explained 68% of the variance in the bio-
physical variables significantly related to whitebark pine
sapling density. A bi-plot of the axis scores illustrated sys-
tematic differences in the multivariate structure of the bio-
physical variables among the mountain ranges, indicating
that each range has a unique physical and climatic envelope
(Fig. 2a). The constrained CCorA ordination was based on
the first 5 axes of the PCO, which together explained 94%
of the variance in the biophysical variables. The CCorA
generally agreed with our correlation analyses (Table 5) and
highlighted the underlying similarities in the relationships
among site biophysical characteristics and whitebark pine
regeneration across our study area (Fig. 2b). Whitebark pine
seedling abundance was correlated at –0.54 with CCorA axis
1 and –0.26 with CCorA axis 2 while sapling abundance
was correlated at –0.59 and 0.19, respectively (Fig. 2b). In
the context of the CCorA ordination, these results indicate
that both seedlings and saplings are generally more abundant
at the sites that were higher, drier, and colder with denser
forests, more whitebark pine, and higher levels of mountain
pine beetle mortality relative to our data set as a whole, and
are less abundant at warmer, wetter sites with greater subal-
pine fir importance. These patterns hold both within and
among the different mountain ranges. The different relation-
ships between seedling and sapling abundance and CCorA
axis 2 indicate that although more whitebark pine regenera-
tion occurred in the relatively colder sites across the land-
scape, within the context of this pattern seedling density
was greater on warmer sites while sapling density was
greater at the cooler sites.
Discussion
The presence of early and advanced whitebark pine
regeneration
The nearly ubiquitous presence of whitebark pine seed-
lings and saplings across our study area was encouraging,
as past landscape-scale assessments of whitebark pine have
reported patchy occurrences of regeneration or abundant
seedlings with few saplings present (Zeglen 2002). The pres-
ence of seedlings at nearly all of our sites reflects two con-
secutive mast years in 2005 and 2006 that occurred across
our study area (Bob Keane, Research Ecologist, USDA Fire
Sciences Laboratory, personal communication, 2007).
Whitebark pine seed germination often lags by 1–2 years
when the seeds are cached by Clark’s nutcrackers (Tomback
et al. 2001a), suggesting these mast events could have pro-
vided the seed source for the abundance of recently emerged
whitebark pine seedlings we observed. However, the ad-
vanced regeneration we documented in the form of saplings
indicates that there have been multiple episodes of success-
ful whitebark pine establishment at our sites over the recent
past.
Abundant seed production would do little for regeneration
without the availability of sites suitable for regeneration.
While whitebark pine regeneration is often associated with
Larson and Kipfmueller 481
Published by NRC Research Press
recently burned or otherwise disturbed settings, our results
are more similar to a recent study in British Columbia that
found comparable densities of whitebark pine seedlings be-
tween recently burned sites and nearby undisturbed settings
(Moody 2006). This suggests that whitebark pine is not lim-
ited to the role of a postfire pioneer species at our study
sites even in the presence of more shade-tolerant species,
such as subalpine fir and mountain hemlock.
The mountain ranges with the lowest densities of regener-
ation illustrate contrasting mechanisms behind these pat-
terns. The stands in the Wallowa Mountains that we
examined were quite open in terms of stand density and to-
tal basal area and would seem to provide ample locations for
whitebark pine regeneration (Tomback 1982), yet regenera-
tion levels were relatively low compared with other sites.
The Wallowa Mountains exhibited the lowest mean rates of
blister rust infection, mountain pine beetle activity, and dis-
turbance frequencies of the ranges included in our study and
had a corresponding greater importance of subalpine fir,
possibly suggesting that these stands were successionally ad-
vanced in the absence of disturbance. The inverse relation-
ship between subalpine fir and whitebark pine regeneration
identified in our correlation analyses and CAP suggests that
subalpine fir may limit whitebark pine regeneration through
resource competition and shading on suitable sites (Keane et
al. 1990). Therefore, the lower rates of regeneration in the
Wallowa Mountains may be the result of advancing succes-
sion due to a general lack of disturbance.
The Salmon River Mountains are climatical ly similar to
the Wallowa Mountains and also exhibit low levels of re-
generation. In the case of the Salmon River Mountains,
however, the low levels of regeneration and greater impor-
tance of subalpine fir are more likely the result of the com-
pounded effects of multiple recent disturbances. Most stands
in the Salmon River Mountains experienced high levels of
mountain pine beetle-related mortality from the late 1980s
to the present in addition to two large fires that burned
across two sites in 1989 and three sites in 1994. Large, in-
frequent disturbances that occur in close temporal succes-
sion such as these events often have different ecological
effects than either disturbance alone (Paine et al. 1998). As
a result, whereas whitebark pine regeneration was positively
correlated with mortality caused by mountain pine beetle
elsewhere in our study area, the fires that burned following
mountain pine beetle activity at these sites may have killed
whatever whitebark pine regeneration was alive at the time
while also killing nearby seed sources that may have sur-
vived the mountain pine beetle outbreaks. In contrast, white-
bark pine regeneration was greater in the mountain ranges
with moderate disturbance frequencies.
These results suggest a disturbance-frequency-dependent
pattern in whitebark pine regeneration that may have impor-
tant implications for the ecological response of whitebark
pine communities across the species range. In particular, the
low levels of whitebark pine regeneration at sites affected
by multiple closely timed disturbance events is a foreboding
pattern in the context of expanding mountain pine beetle
outbreaks (Raffa et al. 2008) and increasing mid- and high-
elevation fire activity in the western United States
(Westerling et al. 2006).
The relationships between whitebark pine regeneration
and biophysical site characteristics
Similar to other tree species that exist across the gradient
from lower subalpine forests to upper subalpine forests, pat-
terns in whitebark pine regeneration reflect both local-scale
factors as well as the overall dominant environmental gra-
dients of regional climate and changing elevation (e.g.,
Table 3. Whitebark pine (Pinus albicaulis) regeneration rates, blister rust rates on alive trees (% BR), frequency of mountain
pine beetle-killed whitebark pine (PIAL-MPB), minimum stand age (Min Age), time since cohort establishment (TSC), and
decadal disturbance frequency (DDF) for each mountain range.
Regeneration rates of Pinus
albicaulis
Range Seedlings/ha Saplings/ha % BR PIAL-MPB Min Age TSC DDF
Cascades 1233±326 703±93 0.11±0.03 0.67±0.06 324±46 137±24 0.12±0.05
Gravelly Range 375±158 467±113 0.63±0.07 0.78±0.06 290±50 124±23 0.09±0.02
Paulina Peak 6086±2113 840±160 0.06±0.03 0.70±0.10 311±28 163±44 0.11±0.03
Pioneer Mountains 3107±1072 866±189 0.41±0.06 0.59±0.10 453±44 279±62 0.08±0.01
Salmon River Mountains 92±29 252±43 0.61±0.10 0.67±0.09 242±31 143±34 0.13±0.01
Wallowa Mountains 215±108 149±33 0.37±0.10 0.34±0.07 442±59 225±49 0.04±0.01
Note: Values are means ± 1 SD.
Table 4. Results of Kruskal–Wallis’ one-way analysis of variance by ranks test for differences in white-
bark pine seedling and sapling densities among mountain ranges.
Seedlings Saplings
Range nMedian Mean rank ZMedian Mean rank Z
Cascades 6 1000 42.6 1.79 720 43.9 1.98
Gravelly Range 8 200 25.1 –0.95 470 31.5 0.17
Paulina Peak 7 6700 49.0 2.98 920 45.2 2.37
Pioneer Mountains 14 900 42.7 2.99 600 42.3 2.88
Salmon River Mountains 12 100 16.1 –3.20 220 20.0 –2.34
Wallowa Mountains 13 100 18.5 –2.81 100 12.8 –4.13
482 Can. J. For. Res. Vol. 40, 2010
Published by NRC Research Press
Pollmann and Veblen 2004). The relationships between
whitebark pine regeneration and biophysical site characteris-
tics that we identified agreed well with the known distribu-
tion of whitebark pine and the niche it occupies (Rehfeldt et
al. 2008). The strong correspondence between axis 1 of our
CCorA and several measures of seasonal and annual temper-
ature and moisture availability (Fig. 2) illustrates whitebark
pine’s ability to regenerate in cold, dry environments and
provides a mechanism for whitebark pine dominance of tim-
berline communities and xeric sites in the subalpine forests
Table 5. Significant Kendall’s trank correlations between bio-
physical site characteristics and whitebark pine seedling and sap-
ling densities, and correlations between biophysical site
characteristics and axes 1 and 2 of the Canonical Correlation
Analysis (CCorA).
Kendall’s tCCorA
Variable tPAxis 1 Axis 2
Seedlings
ABLA IV –0.43 <0.001
Canopy trees/ha 0.42 <0.001
Alive canopy PIAL/ha 0.39 <0.001
pptFall –0.28 0.001
MTWM –0.28 0.001
PICO/ha 0.28 0.001
Dead trees/ha 0.27 0.001
pptSpr –0.27 0.001
GSDD5 –0.24 0.004
SDAY 0.22 0.006
rElev 0.22 0.007
PIAL-MPB 0.19 0.015
GDI 0.17 0.030
Saplings
ABLA IV –0.46 <0.001 0.819 –0.139
PIAL/ha 0.42 <0.001 –0.610 0.354
Dead trees/ha 0.40 <0.001 –0.585 0.466
GSDD5 –0.37 <0.001 0.483 –0.665
MTWM –0.35 <0.001 0.387 –0.645
PIAL-MPB 0.34 <0.001 –0.460 0.630
SDAY 0.33 <0.001 –0.452 0.610
Trees/ha 0.32 <0.001 –0.622 0.007
GDI 0.30 <0.001 –0.271 0.548
FFP –0.30 <0.001 0.447 –0.584
PIAL IV 0.28 0.001 –0.362 0.692
pptSpr –0.26 0.002 0.613 0.404
pptFall –0.25 0.003 0.439 0.325
D100 0.25 0.003 –0.288 0.507
pptAnn –0.24 0.003 0.541 0.251
rElev 0.23 0.004 –0.112 0.207
PICO/ha 0.22 0.008 –0.411 –0.645
pptWin –0.21 0.008 0.475 0.028
Dist Freq 0.19 0.017 –0.169 0.276
Tmax08 –0.16 0.035 0.067 –0.625
TSME/ha 0.16 0.037 –0.374 –0.083
Tmin09 0.16 0.038 –0.454 –0.490
rTRMI –0.15 0.047 0.142 –0.034
Note: In many cases significant correlations were identified between
closely related variables, such as monthly and seasonal precipitation vari-
ables or variations on forest metrics (e.g., relative frequency, relative basal
area, and importance values). In these cases, we listed the single variable
with the strongest relationship. Species codes are as follows: ABLA,
Abies lasiocarpa; PIAL, Pinus albicaulis; PICO, Pinus contorta; TSME,
Tsuga mertensiana. For an explanation of most of the variable codes see
Table 2; others are as follows: PIAL-MPB, Pinus albicaulis killed by
mountain pine beetle; pptFall, mean fall precipitation; pptSpr, mean spring
precipitation; pptAnn, mean annual precipitation; pptWin, mean winter
precipitation; Dist Freq, disturbance frequency; Tmax, mean monthly
maximum temperature; Tmin, mean monthly minimum temperature.
Fig. 2. Ordinations of the biophysical variables significantly corre-
lated to whitebark pine sapling abundance using (a) Principal Co-
ordinates analysis (PCO) and (b) Canonical Correlation Analysis
(CCorA). Site codes in panel aindicate the approximate centroid of
each range in ordination space. Symbols in panel bare scaled by
sapling density. The correlations of the original variables with the
two canonical axes are represented by vectors in panel b. Legend
abbreviations in panel a: CAS, Cascade Range; PAU, Paulina Peak;
WLA, Wallowa Mountains; SRM, Salmon River Mountains; PIO,
Pioneer Mountains; GRA, Gravelly Range. For an explanation of
the abbreviations in panel b, see Table 2 and the Note in Table 5.
Larson and Kipfmueller 483
Published by NRC Research Press
of the Northern Rockies and Pacific Northwest (Arno 2001).
The differing relationships between seedling and sapling
densities and CCorA axis 2 potentially illustrate the differ-
ential effects of the biophysical environment on whitebark
pine germination success versus successful establishment.
McCaughey (1990) found that while warm temperatures
were important for facilitating whitebark pine seed germina-
tion, some of the most common causes of death among
emerging whitebark pine seedlings were heat scorch and
drought. Similarly, Moody (2006) found that whitebark pine
seedlings were more abundant following longer growing
seasons contingent on there being sufficient moisture avail-
able throughout the season. These relationships seem to
play out in our study area, with the greater seedling densities
found at the sites with longer, warmer growing seasons com-
pared with the greater sapling densities at the colder sites
within the context of the overall gradient of axis 1 toward
colder sites in general. The implications of this are that
while seedlings are more likely to emerge at warmer sites,
they are also more likely to suffer heat damage and higher
mortality rates, and therefore seedlings on cooler sites with
lower initial seedling success have higher sapling recruit-
ment rates (Tomback et al. 1993; McCaughey et al. 2009).
This differential response likely affected the spatial pattern-
ing and structure of whitebark pine communities in the past,
and may play an important role in the future dynamics of
whitebark pine forests in the context of global warming.
The strong inverse relationship between whitebark pine
seedling and sapling density and the importance of subalpine
fir at our sites provides an interesting illustration of the
complexity of regeneration dynamics in whitebark pine
communities. Subalpine fir is more tolerant of shade than
whitebark pine but less tolerant of drought and winter desic-
cation, and often depends on whitebark pine to become es-
tablished at harsh sites (Callaway 1998). In moderate sites,
however, subalpine fir often dominates the understory of
whitebark pine forests as they age and transition into later
successional stages (Kipfmueller and Kupfer 2005). Indeed,
subalpine fir was the dominant understory species (based on
importance values) in 22 of the 35 sites in our study at
which it occurred, yet neither subalpine fir importance nor
whitebark pine regeneration densities showed a significant
relationship to stand age (Larson 2009), and the presence of
recently emerged and advanced regeneration at these sites
suggests that whitebark pine regeneration was not yet pre-
cluded from these stands. Campbell and Antos (2003) ob-
served similar patterns of whitebark pine regeneration
throughout the history of several stands in a chronosequence
study of succession in whitebark pine – subalpine fir forests
in British Columbia. Whitebark pine regeneration densities
were significantly different between the landscapes included
in our study, and these patterns may not hold true across the
entire range of whitebark pine, but the presence of white-
bark pine regeneration in later-successional subalpine forests
may play an important role in the persistence of whitebark
pine on the modern landscape, albeit at lower densities.
The role of mountain pine beetles in whitebark pine
regeneration
The declines in whitebark pine forests due to blister rust
are likely unprecedented, as this disease is a novel disturb-
ance with respect to the recent evolutionary history of
whitebark pine, and fire suppression activities are potentially
causing shifts of many whitebark pine forests outside of
their natural range of variability in terms of structure and
composition (Murray et al. 2000; Larson et al. 2009). In
contrast, mountain pine beetle has been a disturbance agent
in whitebark pine forests for millennia (Brunelle et al.
2008), and while recent warming may have exacerbated cur-
rent mountain pine beetle outbreaks (Hicke et al. 2006), this
warmth may not be unprecedented in the evolutionary his-
tory of whitebark pine in North America when compared
with the increased seasonality and temperature extremes as-
sociated with periods such as the Holocene Solar Optimum
(Ruddiman 2000). It would therefore make sense if the tree
species were adapted to occasional severe and widespread
mountain pine beetle outbreaks similar to recent beetle epi-
demics. The strong relationship between rates of whitebark
pine killed by mountain pine beetle and whitebark pine re-
generation density indicate that stand-scale gap-phase dy-
namics may be one response of whitebark pine forests to
mountain pine beetle outbreaks.
Gap dynamics have been extensively studied in forest
ecosystems worldwide (e.g., Platt and Strong 1989 and pa-
pers mentioned therein), yet while the patchy mortality of
most mountain pine beetle outbreaks creates numerous for-
est openings and canopy gaps of varying sizes (Raffa et al.
2008), relatively little research has examined how these dis-
turbances may influence whitebark pine regeneration. In
part, this is due to a broad focus on the historical role of
fire as the dominant disturbance process in most forest types
of western North America (Keane et al. 2002), including
whitebark pine communities (Keane 2001). It also reflects
the uncertainty and relatively limited data available on the
long-term role of mountain pine beetles in whitebark pine
ecosystems. Researchers have observed whitebark pine re-
generation under canopies killed by mountain pine beetle in
the past (Ciesla and Furniss 1975), and while research sug-
gests that warming temperatures are enabling mountain pine
beetle outbreaks to reach whitebark pine forests in climatic
settings that were previously too harsh to support large bee-
tle populations (Hicke et al. 2006), Brunelle et al. (2008)
found evidence that mountain pine beetle outbreaks have oc-
curred in whitebark pine ecosystems since at least the mid
Holocene. In other forest types, mountain pine beetle out-
breaks act as secondary disturbances with strong influences
on patterns in stand development (Sibold et al. 2007). Our
research adds to this growing literature by indicating that
mortality caused by mountain pine beetle in whitebark pine
forests can serve as an effective mechanism for creating
canopy gaps and forest openings that appear to be attractive
seed caching areas for Clark’s nutcrackers (Hutchins and
Lanner 1982; Tomback 1982) and are suitable sites for
whitebark pine regeneration. Additionally, the thinner can-
opy and physical shelter provided to seedlings and saplings
by the presence of standing snags following mountain pine
beetle outbreaks is conducive to higher survival rates for
whitebark pine regeneration in these sites (McCaughey et
al. 2009).
Management implications
The existence of landscape-scale relationships between
484 Can. J. For. Res. Vol. 40, 2010
Published by NRC Research Press
whitebark pine regeneration and the biophysical environ-
ment offer several opportunities to increase the efficacy of
management and restoration activities in whitebark pine
communities. Outplanting of blister rust-resistant seedlings
and saplings is an expensive and labor-intensive endeavor
(Hoff et al. 2001) but is considered one of the more effec-
tive strategies for managing whitebark pine in the presence
of white pine blister rust (Schoettle and Sniezko 2007). In
the context of our research and other recent studies
(McCaughey et al. 2009), targeting stands in colder, drier
settings for outplanting may give the planted whitebark pine
the greatest chance of establishment and eventual matura-
tion. Planting beneath canopies of mature whitebark pine ex-
periencing an active mountain pine beetle outbreak may also
be an effective approach, as the resources made available by
mountain pine beetle disturbances appear to provide an opti-
mal environment for whitebark pine regeneration. Addition-
ally, stands where the mature trees are killed by mountain
pine beetle may be less susceptible to future outbreaks be-
cause of the dearth of larger, living trees that are the pre-
ferred host of beetle infestations (Amman 1972) and,
depending on the susceptibility of the landscape to fire, offer
the longest potential disturbance-free growing period for the
planted trees.
The advanced natural regeneration we observed in gaps
created by mountain pine beetle may also serve as an impor-
tant asset to management aimed at increasing blister rust re-
sistance in whitebark pine. Blister rust infection levels
across our study area were moderate relative to other regions
(Smith and Hoffman 2000; Smith et al. 2008), yet the sus-
ceptibility of early and advanced regeneration to white pine
blister rust (Tomback et al. 1995) may result in differential
mortality among the regeneration we observed with a greater
proportion of surviving seedlings and saplings representing
rust-resistant genotypes. Rust resistance has been docu-
mented to increase rapidly over only a few generations
(Hoff et al. 2001), and the greater levels of regeneration
found at our study sites affected by 20th century mountain
pine beetle outbreaks may act as a catalyst for the develop-
ment of white pine blister rust resistance in whitebark pine.
Natural regeneration in this context may provide a key
mechanism for this foundation species to adapt to its chang-
ing environment and should be closely monitored, as it
could be a critical step in maintaining the presence of white-
bark pine communities in western North America.
Acknowledgements
My deepest thanks to the people that made this research
possible. For their invaluable help in the field, my thanks
go to Kyle Anderson, Adam Berland, Brad Bogard, Neil
Green-Clancey, Noelle Harden, Zach and Mesa Holmboe,
Matt Jacobson, Eric and Shelley Larson, Tony and Donna
Praza, and Danica and Mara Larson, as well as Karen
Arabas, Joe Bowersox, and the Forest Ecology class from
Willamette University. Many thanks to USDA Forest Serv-
ice personnel Carol Aubrey, Kristen Chadwick, Vickey
Erickson, Carly Gibson, Bill Given, Robert Gump, Chris
Jensen, Bob Keane, Al Kyles, Clark Lucas, Robin Shoal,
David Swanson, Sweyn Wall, and Bob Wooley for their
time and assistance in logistics and planning this research.
The research described in this paper was funded in part by
the United States Environmental Protection Agency (EPA)
under the Science to Achieve Results Graduate Fellowship
Program, the National Science Foundation under grant
BCS-0623643, the Carolyn M. Crosby Foundation, the
Mazamas, the Association of American Geographers, the
Mountain Geography Specialty Group of the Association of
American Geographers, the University of Minnesota Gradu-
ate School, and the Department of Geography at the Univer-
sity of Minnesota. EPA has not officially endorsed this
publication, and the views expressed herein may not reflect
the views of the EPA. This manuscript was improved by the
insightful comments of Grant P. Elliott, Lee E. Frelich, Susy
S. Ziegler, and two anonymous reviewers.
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... flexilis E. James), western white pine (P. Whitebark pine is known to be an early successional species in the Rocky Mountains and Pacific Northwest, colonizing recently disturbed sites, including burns and mountain pine beetle attacks, and losing canopy dominance to more shade-tolerant species after 150-400 years without disturbance, especially at lower elevations [7][8][9][10][11][12]. Meyer et al. [13] observed a shift in stand structure toward smaller diameter whitebark pine stems following a mountain pine beetle attack at the June Mt. ...
... Our second objective was to determine whether that relationship was dependent on the position within whitebark pine range, i.e., does proximity to other forest types affect the importance of disturbance to whitebark pine recruitment? Populations are often analyzed as if demography were Whitebark pine is known to be an early successional species in the Rocky Mountains and Pacific Northwest, colonizing recently disturbed sites, including burns and mountain pine beetle attacks, and losing canopy dominance to more shade-tolerant species after 150-400 years without disturbance, especially at lower elevations [7][8][9][10][11][12]. Meyer et al. [13] observed a shift in stand structure toward smaller diameter whitebark pine stems following a mountain pine beetle attack at the June Mt. ...
... 10 ...
Article
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Effective restoration of whitebark pine populations will require a solid understanding of factors affecting seedling recruitment success, which may vary by site and biogeographic region. We examined the relationship between whitebark pine seedling recruitment, disturbance history, and range position in three independent studies in the southern Sierra Nevada, California (CA), USA. In 66 plots broadly distributed across watersheds, we found that whitebark pine seedling density and proportion were greatest at upper elevations, and where canopy cover of whitebark pine was higher (density ranged 0–383 seedlings/ha; x ¯ = 4, σX = 1). Seedling density and proportion were also greater in plots that had recently experienced loss of canopy cover from insects, avalanche, windthrow, or other disturbance effects. In a second study conducted in popular recreational areas, including campgrounds and trailheads, the response of whitebark pine recruitment to disturbance was strongly dependent on the relative position of stands within the range, or proximity to other forest types. Both studies indicated that low to moderate levels of disturbance enhanced whitebark pine recruitment, especially at its range edge, a finding consistent with the early seral status of whitebark observed in previous studies conducted elsewhere in North America. In our third study, a case study at the June Mt. Ski Area, we demonstrate the potential for a downward shift in the whitebark-lodgepole pine ecotone as a result of insect-caused disturbance.
... Further, this strategy is not guaranteed to be successful because it does not ensure complete genetic resistance to white pine blister rust in progeny (McKinney and Tomback 2007). Therefore, natural regeneration and survivorship of seedlings, saplings, and mature trees may determine future population viability (Schoettle and Sniezko 2007, McCaughey et al. 2009, Larson and Kipfmueller 2010, Keane et al. 2012, Hansen et al. 2016. Affiliations: Sara A. Goeking (sgoeking@fs.fed.us), ...
... Seedling density and survival have been positively correlated with above-average precipitation and presence of the shrub Vaccinium scoparium Leiberg ex Coville (Tomback et al. 1993) and negatively related to solar radiation and recent fire-caused mortality of whitebark pines (Lierfallom et al. 2015). Larson and Kipfmueller (2010) assessed regeneration across a wide range of environments, including stands attacked by mountain pine beetle, and found that regeneration was unrelated to stand age but positively related to elevation, precipitation, and recent beetle-caused mortality and negatively related to temperature and dominance of subalpine fir (Abies lasiocarpa (Hook.) Nutt.). ...
... Nutt.). The combination of negative temperature effects and positive elevation and precipitation effects (Larson and Kipfmueller 2010) suggests that seedling density is largely controlled by climate-related factors. Most of these previous studies of natural whitebark pine regeneration have constrained their study domains to stands dominated by whitebark pine, formerly dominated by whitebark pine prior to recent mortality, or adjacent to whitebark pine-dominated stands (e.g., Larson andKipfmueller 2010, Lierfallom et al. 2015). ...
Article
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Whitebark pine (Pinus albicaulis Engelm.) has recently experienced high mortality due to multiple stressors, and future population viability may rely on natural regeneration. We assessed whitebark pine seedling densities throughout the US Rocky Mountains and identified stand, site, and climatic variables related to seedling presence based on data from 1,217 USDA Forest Service Forest Inventory and Analysis plots. Although mean densities were highest in the whitebark pine forest type, 83% of sites with seedlings present occurred in non-whitebark pine forest types, and the highest densities occurred in the lodgepole pine forest type. To identify factors related to whitebark pine seedling presence, we compared the results generated from three statistical models: logistic regression, classification tree, and random forests. All three models identified cover of grouse whortleberry (Vaccinium scoparium Leiberg ex Coville) as an important predictor, two models distinguished live and dead whitebark pine basal area and elevation, and one model recognized seasonal temperature. None of the models identified forest type as an important predictor. Understanding these factors may help managers identify areas where natural regeneration of whitebark pine is likely to occur, including sites in non-whitebark pine forest types.
... and for tree abundance n = 7,975 (Table 1). Juvenile density ranged from 0 to 17,000 seedlings/ha, which was similar to studies from other regions of the species' range (Larson & Kipfmueller, 2010), and adult density ranged from 0 to 3,467 stems/ha. ...
... The coldest climates available across its northern range are the habitats most likely to be currently occupied (Figure 3, Figure 5) (Logan et al., 2010) or that interacts with climate to increase mortality (Wong & Daniels, 2017). Incorporating other drivers such as distance to seed sources (Moody, 2006), the health of seed sources (Leirfallom, Keane, Tomback, & Dobrowski, 2015) as well as masting/episodic seed production (Tomback, Sund, & Hoffmann, 1993), stand and canopy conditions (Larson & Kipfmueller, 2010), and disturbance history (Campbell & Antos, 2003;Keane et al., 1994;Morgan & Bunting, 1990) would improve predictions of abundance across life stages, but especially at the juvenile stage. Other biotic interactions, such as seed predation (Brown & Vellend, 2014), and the absence of important mycorrhizae fungi (Nunez, Horton, & Simberloff, 2009;Wilkinson, 1998) could also be influencing establishment and survival of whitebark pine at both its warm and cold elevational edges, as well as the cold latitudinal edge captured here. ...
Article
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... Continued tree mortality as a result of climate-driven expansion of drought, fire, insects, and non-native pathogens into high-elevation forests will be manifested through the importance of mature tree cover in driving the regeneration response at high elevations. Ongoing MPB-and WPBR-induced mortality across the species' range may have variable impacts on whitebark pine regeneration response, even promoting regeneration in some sites (Larson & Kipfmueller, 2010;Meyer et al., 2016). Areas of greater snowpack within the study area (e.g. ...
Article
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Aim The persistence potential of forests under rapid climate change will depend on species‐specific tolerances to increasing growing season soil moisture stress as snowpack declines. High‐elevation tree species may be particularly vulnerable to increasing water stress and associated changes to disturbance regimes because they occur at the environmental margins of tree distributions and are considered snowpack dependent. Here, we evaluate the interacting effects of climate, disturbance, and microsite conditions on tree regeneration in high‐elevation, migration‐limited pines that have experienced recent disturbance‐induced tree mortality. Location Great Basin (California and Nevada), USA Taxon Gymnosperms; Pinaceae Methods We used field observations from 70 sites that varied in climate, disturbance, and local site conditions across semi‐arid, high‐elevation forests of the Great Basin. We employed structural equation models to evaluate how climate and disturbance interact with microsite conditions to influence regeneration. Results We found a broad range of establishment conditions for high‐elevation conifers—whitebark, limber, and bristlecone pines—across climatic and disturbance gradients in the Great Basin, but our research detected clear differences in the regeneration niche for each species that may lead to differential survival as climate and disturbance conditions continue to change. Regeneration of whitebark and bristlecone pines diverged in their responses to spring snowpack conditions, with whitebark pine increasing and bristlecone pine decreasing with greater spring snowpack. Limber pine regenerated across a range of climatic and landscape conditions, and this generalist strategy may be advantageous if future climate and disturbance conditions exceed tolerances of more specialized high‐elevation conifers. Main Conclusions Our findings highlight the critical role that spring snowpack, and consequently growing season soil moisture, plays in determining the persistence potential of high‐elevation conifers. However, this role varies among species and thus may drive compositional changes as earlier snowmelt drives soil moisture declines across mountainous landscapes of the western United States.
... Fuel hazard hot spots increased and shifted across the landscape over time, then fire hazard hot spots were reduced approximately two to four years following MPB outbreak ( Fig. 5C; O2-O3). MPB-affected stands can provide a suitable environment for WBP regeneration if seed sources are available (Larson and Kipfmueller, 2010), but a large-scale reduction in seed-producing trees, the impact of blister rust on seedlings and saplings, and the uncertain effects of climate change place the future of WBP forests in western North America in peril. Active management and restoration, including planting WBP seedlings or planting rust-resistant trees in MPB-affected stands, may be needed to maintain WBP populations. ...
Article
Mountain pine beetle (MPB; Dendroctonus ponderosae Hopkins) causes extensive tree mortality in whitebark pine (Pinus albicaulis Engelm) forests. Previous studies conducted in lodgepole pine (Pinus contorta Douglas), Douglas-fir (Pseudotsuga menziesii (mirb.) Franco), and Engelmann spruce (Picea engelmanni Parry ex. Engelm) have shown that litter, duff, and 1-h (<0.64 cm) and 10-h (0.64-2.54 cm) time lag fuels are altered significantly from MPB outbreaks, while coarse woody fuels are affected over a longer time frame. MPB activity in conifer stands also alters foliar fuel moisture content over the course of the bark beetle rotation. This study evaluated changes to fine surface fuels and foliar fuel moisture in and under whitebark pine trees infested by MPB at two sites in Montana and Wyoming, USA. Fuel loads and foliar moisture were measured for crown condition classes of green trees (healthy), red trees (within two years since initial MPB attack with at least 50% of needles remaining), and gray trees (more than two years since attack with approximately 15% to 45% needles remaining). Tree locations and condition class were mapped using 2011, 2013, and 2015 NAIP imagery, and spatial point patterns were identified. Duff depths were significantly shallower beneath green trees (10.7-11.9 mm) than red (16.7-17.7 mm) and gray (13.9-16.1 mm) trees. Foliar fuel moisture content was altered dramatically across crown condition classes. Red needled trees had the lowest fuel moisture content, which was less than 18%. Point pattern hot spot analysis revealed increased (hot-spots) fuel hazard in trees 2-3 years post MPB attack, and decreased fuel hazard (cold-spots) in trees more than 3 years after MPB attack because foliage fell from trees and left larger diameter aerial fuels which were less likely to ignite. MPB-attacked trees were often clustered, and thus fuels hazard was not uniform across the landscape following MPB attack.
... This is perhaps due to the tendency for these species to occupy sites where moisture is non-limiting (Arno and Habeck 1972;Arno and Hoff 1989) and indicates that, at least historically, adequate moisture has been available for rapid establishment of the species to occur during periods of increased summer warmth. The insensitivity of P. albicaulis to precipitation variables has also been identified in other studies but appears to be context dependent; Goeking et al. (2019) found no relationship between summer precipitation and P. albicaulis seedling density in their surveys of seedling abundance (US Rocky Mountains) whereas Larson and Kipfmueller (2010) found regeneration to be negatively related to moisture availability (Northwestern USA). That P. albicaulis was not historically dependent on periods of increased precipitation for successful establishment in our study region does not, however, preclude the possibility that moisture limitations may play a role in future successful establishment. ...
Article
Full-text available
The distributions of many high-elevation tree species have shifted as a result of recent climate change; however, there is substantial variability in the movement of alpine treelines at local to regional scales. In this study, we derive records of tree growth and establishment from nine alpine treeline ecotones in the Canadian Rocky Mountains, characterise the influence of seasonal climate variables on four tree species (Abies lasiocarpa, Larix lyallii, Picea engelmannii, Pinus albicaulis) and estimate the degree to which treeline movement in the twentieth century has lagged or exceeded the rate predicted by recent temperature warming. The growth and establishment records revealed a widespread increase in radial growth, establishment frequency and stand density beginning in the mid-twentieth century. Coinciding with a period of warming summer temperatures and favourable moisture availability, these changes appear to have supported upslope treeline advance at all sites (range, 0.23–2.00 m/year; mean, 0.83 + 0.67 m/year). However, relationships with seasonal climate variables varied between species, and the rates of treeline movement lagged those of temperature warming in most cases. These results indicate that future climate change impacts on treelines in the region are likely to be moderated by species composition and to occur more slowly than anticipated based on temperature warming alone.
... 62). First, it could be that lower portions of whitebark pine seral sites may be too harsh (i.e., high radiation loads, drier, warmer) for survival of whitebark pine seedlings in the majority of years, thereby limiting effective natural regeneration (Larson and Kipfmueller 2010;Lonergan et al. 2013;McCaughey and Weaver 1990). Second, the lower portions of seral sites, especially those on southern slopes, may have warmer climates that facilitate rapid successional replacement of whitebark pine by subalpine fir, spruce, and perhaps a suite of lower elevation species, such as Douglas-fir, especially in areas that already experience abundant precipitation (Arno and Hoff 1990). ...
Technical Report
Full-text available
A review of whitebark pine restoration methods and approaches with respect to future climates.
... Early postfire regeneration (within the first two decades) affected structural trajectories of four widespread conifer species for decades to centuries in stands across a wide gradient of environmental conditions. Regeneration processes, such as seed supply, dispersal, establishment, and early seedling survival, are often highly sensitive to changes in disturbance regimes and environmental fluctuations (Kipfmueller and Kupfer, 2005;Larson and Kipfmueller, 2010;Harvey et al., 2016b;Kemp et al., 2016;Hansen et al., 2018;Stevens-Rumann et al., 2018). Early regeneration densities may forecast long-term trajectories in ecosystems that experience periodic high-severity disturbances (Turner et al., 1998), although it may be necessary to consider more than just the first few years of establishment (e.g., Peterson and Pickett, 1995;Gill et al., 2017). ...
Article
High-severity, infrequent fires in forests shape landscape mosaics of stand age and structure for decades to centuries, and forest structure can vary substantially even among same-aged stands. This variability among stand structures can affect landscape-scale carbon and nitrogen cycling, wildlife habitat availability, and vulnerability to subsequent disturbances. We used an individual-based forest process model (iLand) to ask: Over 300 years of postfire stand development, how does variation in early regeneration densities versus abiotic conditions influence among-stand structural variability for four conifer species widespread in western North America? We parameterized iLand for lodgepole pine (Pinus contorta var. latifolia), Douglas-fir (Pseudotsuga menziesii var. glauca), Engelmann spruce (Picea engelmannii), and subalpine fir (Abies lasiocarpa) in Greater Yellowstone (USA). Simulations were initialized with field data on regeneration following stand-replacing fires, and stand development was simulated under historical climatic conditions without further disturbance. Stand structure was characterized by stand density and basal area. Stands became more similar in structure as time since fire increased. Basal area converged more rapidly among stands than tree density for Douglas-fir and lodgepole pine, but not for subalpine fir and Engelmann spruce. For all species, regeneration-driven variation in stand density persisted for at least 99 years postfire, and for lodgepole pine, early regeneration densities dictated among-stand variation for 217 years. Over time, stands shifted from competition-driven convergence to environment-driven divergence, in which variability among stands was maintained or increased. The relative importance of drivers of stand structural variability differed between density and basal area and among species due to differential species traits, growth rates, and sensitivity to intraspecific competition versus abiotic conditions. Understanding dynamics of postfire stand development is increasingly important for anticipating future landscape patterns as fire activity increases.
... Many factors can interact with and influence regeneration species and densities (Gray et al., 2005;Puhlick et al., 2012;Bataineh et al., 2013), making mixed species regeneration particularly difficult to predict (Fisichelli et al., 2013;Crotteau et al., 2014). Other studies on related fiveneedle pine species including P. albicaulis, P. monticola and P. strobus have identified source strength (overstory BA, number of cones), climate variables, light, soils (Dovciak et al., 2003;Maloney, 2014), elevation and aspect (Larson and Kipfmueller, 2010) as good predictors of regeneration. Our analyses suggest that understory and overstory environments were more important in predicting SWWP regeneration than stand-level abiotic factors such as climate variables, elevation or aspect. ...
Article
Modelling natural regeneration is complex, and both natural and anthropogenic disturbances can alter forest trajectories. Pinus strobiformis (southwestern white pine, SWWP) is an important component of mixed conifer forests in the Southwest and management recommendations related to natural and planted regenerations are needed to guide conservation of SWWP in the face of an invasive disease (white pine blister rust, WPBR). Regeneration was surveyed across six mountain ranges, three silviculture treatments and two levels of disease severity in the Southwest US. Key findings were: (1) SWWP regeneration in stands with no recent management (<20 years) and high disease severity had unsustainable WPBR infection, (2) SWWP regeneration was less abundant but less likely to be infected in stands with recent management, (3) stands with high disease severity had fewer SWWP seedlings than stands with no or low disease severity and (4) SWWP regeneration densities were best predicted by other understory species abundance. We recommend silviculture treatments that reduce basal area to 9-10 m²ha⁻¹ and leave large canopy openings to enhance natural SWWP regeneration. Without creating conditions for disease-free regeneration to reach reproductive maturity, some stands may lose SWWP as an overstory component. Results may help refine SWWP management guidelines and expand conservation efforts in forests threatened by WPBR. © Institute of Chartered Foresters, 2018. All rights reserved. For Permissions, please e-mail: [email protected]
Article
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(1) Clark's nutcrackers (Nucifraga columbiana) store a mean of only 3.7 whitebark pine (Pinus albicaulis) seeds per cache, which reduces competition for moisture and space. The mean depth at which seeds are stored, 2.0 cm, is compatible with germination requirements, and many sites selected appear suitable for seed germination. (2) One nutcracker stores about 32 000 whitebark pine seeds at subalpine elevations each year, which represent 3-5 times its energetic requirements. Although parent nutcrackers feed stored seeds to juveniles, in some years there is probably an excess of seeds stored by the population as a whole. (3) Experimental results suggest that seeds retrieved from nutcracker caches are as viable as seeds extracted by hand from cones and that seedlings originating in nutcracker caches have a good survival rate: 56% over the first year and 25% by the fourth year. (4) In comparison with Clark's nutcracker, alternative disperal agents, i.e. rodents and cone disintegration, disperse fewer seeds, disperse seeds shorter distances from parent trees, place seeds in sites less suitable for germination, and/or make large seed caches which lower reproductive potential. Nutcrackers disseminate seeds throughout the subalpine habitat and are, in part, responsible for the `pioneering' status of whitebark pine. (5) The evolution of wingless seeds and indehiscent cones in the Cembra pine group was probably a consequence of seed dispersal by an ancestral nutcracker form. It appears that the Clark's nutcracker--whitebark pine interaction is both coevolved and mutualistic.
Article
This article incorporates new information into previous whitebark pine guidelines for planting prescriptions. Earlier 2006 guidelines were developed based on review of general literature, research studies, field observations, and standard US Forest Service survival surveys of high-elevation whitebark pine plantations. A recent study of biotic and abiotic factors affecting survival in whitebark pine plantations was conducted to determine survival rates over time and over a wide range of geographic locations. In these revised guidelines, we recommend reducing or avoiding overstory and understory competition, avoiding swales or frost pockets, providing shade and wind protection, protecting seedlings from heavy snow loads and soil movement, providing adequate growing space, avoiding sites with lodgepole or mixing with other tree species, and avoiding planting next to snags.
Article
Pinus albicaulis has large, energy-rich, wingless seeds that are not wind dispersable and indehiscent cones that retain their matured seeds within. Scales are easily broken off the cone axis, leaving many of the seeds exposed and held in the core of the cone. Cones are sessile on ascending limbs, and therefore conspicuous when viewed from above. These characteristics are adaptations to the foraging activities of Nucifraga columbiana, which removes seeds from cones and stores them in subsoil caches, thus permitting them to germinate. Speciation of the Cembrae pines may have occurred through nutcracker-mediated selection exerted on conventional white pine antecedents.-Author
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Whitebark pine (Pinus albicaulis) is a high elevation stone pine characterized by heavy, wingless seeds that are primarily dispersed by the Clark’s nutcracker (Nucifraga columbiana). The relationship between seed dispersal, spatial distribution, and site characteristics of whitebark pine was studied in the timberline ecotone of the Beartooth Plateau, Montana and Wyoming. The study focused on regeneration patterns and prevailing microsite conditions which may limit or promote germination and survival of whitebark pine at its upper elevational limit. Regeneration of Engelmann spruce (Picea engelmannii)and subalpine fir (Abies lasiocarpa) was poor in both study areas. Juvenile whitebark pines were more abundant in areas with moderate to late snow release. Only few young whitebark pine seedlings and germinants were located on Tibbs Butte, whereas in the Wyoming Creek study area, young whitebark pine seedlings clusters (≤ 3 years) were present in all transects. Regeneration densities inside and leeward of the woodland were higher than on the windward side. Regeneration results were not consistent with reported caching preferences of the Clark’s nutcracker. Sites with moderate to long snow cover, leeward of tree groups or in depressions, appear unfavorable for caching, because of restricted access to stored seeds, but were favorable for germination and survival of whitebark pine. Only nutcracker caches that are not retrieved and that are established in relatively moist and protected microsites contribute to recruitment. The data of this study show that regeneration of whitebark pine does occur in parts of the timberline ecotone. Recruitment in exposed sites appears unsuccessful. Tree regeneration in timberline ecotones with continental climate character may require the additional moisture found in snowdrifts of small depressions or tree groups.
Article
The relative importance of competition and facilitation has been hypothesized to change with variation in abiotic conditions. I examined the relative importance of competition and facilitation along elevation gradients in the northern Rocky Mountains where Pinus albicaulis and Abies lasiocarpa dominate the overstory. At lower elevations and in more sheltered sites, A. lasiocarpa seedlings, saplings, and trees were not spatially associated with mature P. albicaulis, whereas at high-elevation sites along exposed ridges near timberline A. lasiocarpa were highly aggregated around mature P. albicaulis. I also compared growth rates of A. lasiocarpa trees before and after the death of adjacent P. albicaulis to growth rates of A. lasiocarpa in the same years but adjacent to living trees. In the Bitterroot Mts. A. lasiocarpa responded positively to the death of adjacent P. albicaulis at low-elevation sites (7% increase), but negatively at high-elevation sites (24% decrease). This suggests that facilitation was more important at timberline sites characterized by abiotic extremes and competition was more important in more moderate abiotic conditions. At high-elevation sites in both mountain ranges, large A. lasiocarpa were 2-4 times more aggregated with P. albicaulis than A. lasiocarpa seedlings. At the high-elevation site in the Bitterroots, growth rates of large A. lasiocarpa were significantly lower in open microsites than when trees were adjacent to either living or dead P. albicaulis. In contrast, growth rates of small saplings did not differ among these microsites. Stronger facilitative effects on mature trees than on seedlings or saplings may develop because the winter snowpack protects small A. lasiocarpa from blowing ice and snow. After trees grow above the snowpack shelter from large P. albicaulis may be crucial. These results emphasize the importance of studying interspecific interactions over a range of conditions; in these forests both positive and negative interactions occur between A. lasiocarpa and P. albicaulis, but their relative importance depends on abiotic conditions and plant life history stage.
Article
Pinus albicaulis (whitebark pine) is an important tree species in subalpine forests of the Northern Rocky Mountains. Populations have been declining at unprecedented rates due to the introduction of an exotic pathogen and fire suppression. We initiated this study to evaluate historical trends in Pinus albicaulis abundance along with associated subalpine conifers within a small biogeographically disjunct mountain range. The central objective was to estimate historic trends in subalpine forest composition and structure at the species and community scales. Reconstruction of forest stands reveals an 85% increase in tree volume among all species since the 1870s. Pinus albicaulis has historically dominated most stands associated with Abies bifolia (subalpine fir) and Picea engelmannii (Engelmann spruce) but dominance has shifted to these late-seral species for most of the study area since the early 1990s. We estimate, that since 1753, nearly 50% of the study area has shifted to later successional stages while only 3% has receded to earlier stages. We discuss the implications for Pinus albicaulis and suggest that careful reintroduction of fire can aid in the maintenance of ecological integrity at the community and landscape scales.