A multicentury dendrochronological reconstruction of western spruce budworm outbreaks in the Okanogan Highlands, northeastern Washington

Abstract

The western spruce budworm (Choristoneura occidentalis occidentalis Freeman) is recognized as the most ecologically and economically damaging defoliator in western North America. Synchronous western spruce budworm outbreaks can occur over much of a host species’ range, causing widespread limb and tree mortality, regeneration delays, and reduction in tree growth rates. Observational outbreak records in northern Washington State extend back only to the mid-20th century, limiting our understanding of this species’ long-term population dynamics. In this study, we used dendrochronological methods to reconstruct multicentury outbreak records at four sites in the Okanogan Highlands of northeastern Washington State. We assessed long-term changes in outbreak patterns and tested moisture availability as a potential driving factor of western spruce budworm population dynamics. Outbreak synchrony was found to increase after the late 19th century, especially for high-intensity outbreaks, possibly due to anthropogenic factors. Moisture availability records show that outbreaks tend to occur at the end of droughts. As the variability of climate conditions is projected to increase, trending towards warm and dry summer conditions, the intensity and frequency of high-intensity western spruce budworm outbreaks may increase as well.

Full text

ARTICLE
A multicentury dendrochronological reconstruction of western
spruce budworm outbreaks in the Okanogan Highlands,
northeastern Washington
Todd M. Ellis and Aquila Flower
Abstract: The western spruce budworm (Choristoneura occidentalis occidentalis Freeman) is recognized as the most ecologically and
economically damaging defoliator in western North America. Synchronous western spruce budworm outbreaks can occur over
much of a host species’ range, causing widespread limb and tree mortality, regeneration delays, and reduction in tree growth
rates. Observational outbreak records in northern Washington State extend back only to the mid-20th century, limiting our
understanding of this species’ long-term population dynamics. In this study, we used dendrochronological methods to recon-
struct multicentury outbreak records at four sites in the Okanogan Highlands of northeastern Washington State. We assessed
long-term changes in outbreak patterns and tested moisture availability as a potential driving factor of western spruce budworm
population dynamics. Outbreak synchrony was found to increase after the late 19th century, especially for high-intensity
outbreaks, possibly due to anthropogenic factors. Moisture availability records show that outbreaks tend to occur at the end of
droughts. As the variability of climate conditions is projected to increase, trending towards warm and dry summer conditions,
the intensity and frequency of high-intensity western spruce budworm outbreaks may increase as well.
Key words: dendrochronology, dendroecology, drought, Pacific Northwest, western spruce budworm.
Résumé : La tordeuse occidentale de l’épinette (Choristoneura occidentalis occidentalis Freeman) est considérée comme l’insecte
défoliateur qui cause le plus de dommages écologiques et économiques dans l’ouest de l’Amérique du Nord. Des épidémies
synchrones de la tordeuse occidentale de l’épinette peuvent survenir presque partout dans l’aire de répartition des espèces hôtes,
causant beaucoup de mortalité des branches et des arbres, des retards dans la régénération et une réduction du taux de
croissance des arbres. Les données d’observation des épidémies dans le nord de l’État de Washington remontent seulement au
milieu du 20e siècle, ce qui limite notre compréhension de la dynamique de population a
`long terme de cette espèce. Dans cette
étude nous avons utilisé des méthodes dendrochronologiques pour reconstituer des données d’épidémie sur plusieurs siècles a
`
quatre endroits dans les hautes terres d’Okanagan au nord-est de l’État de Washington. Nous avons évalué les changements a
`
long terme dans le comportement des épidémies et testé la disponibilité de l’humidité en tant que facteur déterminant de la
dynamique de population de la tordeuse occidentale de l’épinette. Nous avons trouvé que le synchronisme des épidémies a
augmenté après la fin du 19e siècle, particulièrement dans le cas des épidémies sévères, possiblement a
`cause de facteurs
anthropiques. Les données sur la disponibilité de l’humidité montrent que les épidémies ont tendance a
`survenir a
`la fin des
périodes de sécheresse. Étant donné qu’on anticipe une augmentation de la variabilité des conditions climatiques, avec une
tendance vers des étés chauds et secs, l’intensité et la fréquence des épidémies sévères de tordeuse occidentale de l’épinette
pourraient aussi augmenter. [Traduit par la Rédaction]
Mots-clés : dendrochronologie, dendroécologie, sécheresse, Pacific Northwest, tordeuse occidentale de l’épinette.
1. Introduction
Western spruce budworm (Choristoneura occidentalis occidentalis
Freeman) is recognized as an ecologically and economically signif-
icant defoliating insect in western North America (Fellin and
Dewey 1982;Jenkins 2015). Regionally synchronous, decade-long
outbreaks over large areas lead to widespread ecological resource
impacts. However, the causal mechanisms driving this species’
outbreak patterns and population dynamics remain under-
explored, with results often pointing to contradictory mechanisms.
An understanding of the western spruce budworm’s (WSB) popu-
lation dynamics is necessary to understand ecosystem dynamics,
predict climate change effects, and mitigate ecological and re-
source management impacts. Multicentury records are needed to
establish accurate outbreak histories and shed light on climatic
drivers of WSB’s outbreak dynamics. While observational records
of WSB activity are only available back to the mid-20th century,
variations in the width of annual tree rings can serve as a proxy
record of WSB defoliation. Dendrochronological records have
been used to reconstruct multicentury histories of WSB outbreak
dynamics in the American Southwest (Swetnam and Lynch 1993),
central Rocky Mountains (Ryerson et al. 2003), and the Pacific
Northwest, including British Columbia (B.C.), Montana, Idaho,
and Oregon (Swetnam et al. 1995;Flower et al. 2014a;Axelson et al.
2015). A prominent gap in the spatial coverage of these outbreak
records exists in northern Washington State. In this paper, we
present a dendrochronological reconstruction of WSB outbreaks
in Washington State’s Okanogan Highlands region.
The WSB consumes host foliage with a preference for current-
year buds, staminate flowers, and developing cones, causing re-
Received 15 September 2016. Accepted 14 June 2017.
T.M. Ellis and A. Flower. Department of Environmental Studies, Western Washington University, 516 High Street, MS 9085, Bellingham, WA 98225, USA.
Corresponding author: Todd Ellis (email: toddellis.wa@gmail.com).
Copyright remains with the author(s) or their institution(s). Permission for reuse (free in most cases) can be obtained from RightsLink.
1266
Can. J. For. Res. 47: 1266–1277 (2017) dx.doi.org/10.1139/cjfr-2016-0399 Published at www.nrcresearchpress.com/cjfr on 14 June 2017.
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duction in growth rates, regeneration delays, and limb and tree
mortality after several years of repeated defoliation (Alfaro et al.
1982;Fellin and Dewey 1982). Douglas-fir (Pseudotsuga menziesii
(Mirb.) Franco) and true firs (Abies spp.) are the WSB’s principal
host species (Fellin and Dewey 1982). Host stands undergoing an
outbreak suffer a loss of biomass, increased rates of topkill, stem
deformities, and tree mortality, especially of saplings and seed-
lings (Fellin and Dewey 1982;Maclauchlan et al. 2006), and may
have increased susceptibility to subsequent insect outbreaks and
pathogens (Alfaro et al. 1982). Repeated outbreaks ultimately
modify the composition and structure of forests, redistributing
the biomass and resources of susceptible host stands by removing
photosynthetic tissue and reducing the local carbohydrate sup-
plies necessary for continued growth (Alfaro et al. 1982). For ex-
ample, Alfaro et al. (1982)’s study found that four outbreaks over
roughly 85 years reduced the stand’s potential radial growth by
about 12%, with mortality rates ranging from 4.5% among mature
trees with a dominant canopy position to 39% among suppressed
understory trees.
In the Pacific Northwest, WSB infestations are frequent in many
coniferous stands, with insect populations often continuously
present at low endemic levels (Fellin and Dewey 1982;Wickman
1992). Radial growth impacts from WSB outbreak defoliation tend
to last, on average, between 11 and 15 years (Lynch 2007). Aerial
survey records suggest even shorter intervals of WSB outbreaks,
lasting as few as 1 to 2 years in some regions (USDA Forest Service
2014). Quiescent period durations also vary across impacted re-
gions, with an average of 32 to 40 years between outbreaks
(Swetnam et al. 1995;Lynch 2007).
WSB outbreaks tend to occur synchronously over large areas
of the primary host species’ range (Ryerson et al. 2003;Flower
et al. 2014a;Flower 2016). Large regions of synchronous or near-
synchronous WSB outbreaks are usually attributed to one or more
of the following factors: adult moth dispersal, exogenous stochas-
tic factors such as climate, or trophic interactions with similarly
synchronous or mobile populations (Peltonen et al. 2002). Disper-
sal capabilities strongly influence synchrony of population fluctu-
ations at finer spatial scales (i.e., under 200 km), whereas climatic
controls may be more a more important driver of synchrony at
coarse spatial scales, though the mechanisms behind observed
patterns of synchrony are still not well understood (Peltonen et al.
2002).
Over the course of the 20th century, some regions have shown
increasing outbreak synchrony, severity, and (or) intensity, possi-
bly as a result of human impact (Swetnam and Lynch 1993;
Swetnam et al. 1995;Ryerson et al. 2003;Campbell et al. 2006;
Flower et al. 2014a,2014b). The expansion of the extent and pre-
dominance of WSB’s host species (both Douglas-fir and true firs)
due to historical human impacts (Hessburg et al. 1994;Keane et al.
2002) may be linked to these changing outbreak dynamics. Selec-
tive harvesting of competing species, fire exclusion, and livestock
grazing are thought to have favored the establishment of WSB’s
host species (Wickman 1992).
Climatic changes may have also played a role in these changing
WSB outbreak dynamics, and climatic variables are thought to be
a primary driving force of WSB population dynamics (Campbell
1993;Swetnam and Lynch 1993;Flower et al. 2014a). Fluctuations
in moisture availability are seen as the most important variable in
effecting changes to WSB population dynamics, with reduced
moisture availability and, thus, reduced needle moisture content
linked to enhanced larval survival, growth, and reproductive rates
(Clancy 1991;Campbell 1993). In particular, the combination of
increased moisture availability following drought conditions may
improve both the quality and quantity of the WSB’s preferred
foliage during spring emergence (Flower et al. 2014a;Flower 2016).
Previous studies have reported inconsistent relationships be-
tween WSB outbreaks and climatic conditions, suggesting that
the WSB’s response to climate variables may be regionally vari-
able. For instance, Swetnam and Lynch (1993) found that high
spring precipitation was an influencing factor in outbreak timing
in Colorado, while Flower et al. (2014a)found that an increase in
moisture stress was necessary in initiating outbreaks in Oregon,
Idaho, and Montana. The potential range of the WSB includes a
variety of climatic zones, with controlling climatic variables likely
differing based on local- and regional-level climate. Local records
are thus needed to assess climatic influences on WSB population
dynamics in understudied areas such as northern Washington
State.
The development of multicentury reconstructions contributes
to the development of forest management strategies that can cope
with the economic and ecological impacts of defoliating insects
(Shepherd 1994). The purpose of this study is to uncover the
Okanogan Highlands landscape’s history of WSB outbreaks, con-
necting an important geographic gap to surrounding recon-
structed outbreak records (e.g., Flower et al. 2014a;Axelson et al.
2015). We characterize the frequency, periodicity, levels of syn-
chrony, and intensity of the landscape’s outbreak history. Using
these data with historical and reconstructed climate records, we
enhance our understanding of how moisture availability influ-
ences the WSB’s population dynamics and how changing climatic
conditions may alter future WSB outbreak patterns.
2. Materials and methods
2.1. Study area
We collected samples at six sites in the Okanogan Highlands of
Okanogan National Forest in August and October 2014 (Fig. 1). The
Okanogan Highlands are characterized by an arid, shrub–steppe
environment, with vegetation dominated by Douglas-fir, with
lesser amounts of ponderosa pine (Pinus ponderosa Douglas ex
P. and C. Lawson), western larch (Larix occidentalis Nutt.), and grand fir
(Abies grandis (Dougl. ex D. Don) Lindl.; McNab and Avers 1994).
Elevations at our sites ranged between 1000 and 1600 m. The
geological setting of most study sites was gneiss bedrock, with the
easternmost host site identified as basalt (Lasmanis and Cheney
1994). Using ClimateWNA’s 30-year climate normals for 1981–
2010, our site records report average temperatures from –6.2 °C to
15.8 °C in the coldest and warmest months, respectively; average
annual precipitation was recorded as 451 mm (±62 mm), with
175 mm (±5.2 mm) occurring during summer months (Wang et al.
2012).
2.2. Sampling strategy
We collected samples at paired host and non-host sites. Samples
collected at non-host sites were used to create a control chronol-
ogy. This approach allowed us to isolate the defoliation signal
contained in host tree-ring chronologies. We chose Douglas-fir as
a host species due to its wide range in the Okanogan Highlands
and its susceptibility to WSB outbreaks (Mason et al. 1997). We
chose ponderosa pine as our non-host species. Douglas-fir and
ponderosa pine have overlapping geographic ranges and similar
responses to climate (Watson and Luckman 2002;Chen et al.
2010), but ponderosa pine is rarely defoliated by the WSB (Fellin
and Dewey 1982).
We selected potential study areas with a history of frequent
WSB outbreaks based on annual USFS Insect and Disease Survey
data dating back to 1947 (Williams and Birdsey 2003;USDA Forest
Service 2014). Within those potential study areas, we selected spe-
cific study sites using satellite imagery and in situ evidence. We
selectively targeted sites separated by significant topographic fea-
tures such as mountains or valleys to insure adequate spatial cov-
erage. We targeted stands with multicentury records, with the
oldest trees ideally dating to at least 300 years (Table 1). We
avoided host and non-host stands with extensive recent distur-
bances such as logging or fire damage.
Ellis and Flower 1267
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We extracted two increment cores per tree. We avoided reac-
tion wood by coring parallel to the slope contour at 1.3 m aboveg-
round, except where impossible due to difficult topography. We
sampled 15–20 trees from each of our four host stands for a total
of 69 trees (Table 1). Within sites, we selectively sampled based on
visual assessment, using criteria that included old-age cues such
as flattened tops, spiral-grained bark, large lower limbs, and di-
ameter at breast height of at least 40 cm. We avoided samples that
included any indication of significant damage (e.g., fire scars) that
could potentially distort the growth patterns.
For non-host stands, we sampled between 6 and 17 trees from
three sites to maximize the visible impacts of defoliation (Table 1).
To produce the longest possible record, we collected non-host
samples with the intention of creating a single landscape-wide
chronology for use with each host site. Monospecific non-host
stands were preferentially targeted to avoid any growth release
from species affected by defoliation or competition (Swetnam
et al. 1995). Old-growth ponderosa pine stands are, however, ag-
gressively maintained by the USFS, which selectively harvests
young growth around older pine trees (P. Nash, personal corre-
spondence, 2014). Because of these issues, the age of non-host
stands superseded the importance of monospecificity and we in-
clude six trees from our Turner Lake site despite the presence of
Douglas-fir.
2.3. Sample preparation and laboratory analysis
We prepared our samples using standard dendrochronological
techniques (Speer 2010). We dried and glued core samples to
wooden core mounts before surfacing with 120-, 220-, 320-, 400-,
and 600-grit sandpaper. First, each sample was visually crossdated
from the bark inwards using a microscope and then was scanned
and measured to the nearest 0.001 mm using Cybis’ CooRecorder
and CDendro software (Larsson and Larsson 2014). We used
CDendro to visually identify known outbreak periods (Swetnam
et al. 1995) and create master chronologies for each host and
non-host site. CDendro allowed for the creation of a master chro-
nology to be used with any sample measurements, minimizing
the errors caused by our visual interpretation (Larsson and
Larsson 2014). We statistically crossdated our ring-width chronol-
ogies using the R package dplR (Bunn 2008;R Core Team 2013).
We used the dplR package to detrend raw measurements for
host and non-host sites using a 100-year cubic smoothing spline
Fig. 1. Location of host (Douglas-fir) and non-host (ponderosa pine) sites within the Okanogan Highlands. Significant local features include
the highest peak, Mount Bonaparte, immediately east of site MPD, and the Aeneas Valley dividing our southern sites from our northern
locations. Shaded region on the inset map represents distribution of Douglas-fir, provided by Little (1971). Digital elevation model courtesy of
the U.S. Geological Survey.
Table 1. Site and chronology characteristics for our four host (Douglas-fir) sites and three non-host (ponderosa pine)
sites in the Okanogan Highlands.
Site Latitude Longitude Elevation (m)
No. of
trees DBH (cm)
Oldest
record
EPS
(Pearson)
Interseries
r(Pearson)
Host (Douglas-fir)
MPD 48.786 –119.243 1359 16 86.1 (±16.8) 1685 0.933 0.686
SMD 48.561 –119.172 1379 18 70.7 (±15.4) 1796 0.943 0.780
TMD 48.552 –119.225 1599 20 75.0 (±14.5) 1685 0.936 0.650
VLD 48.825 –118.927 1286 15 92.5 (±21.5) 1719 0.965 0.760
Non-host (ponderosa pine)
DCP 48.528 –119.029 1003 17 66.2 (±8.1) 1685 0.942 0.627
TLP 48.672 –118.981 1334 6 66.3 (±13.3) 1685 0.847 0.720
VLP 48.824 –118.927 1274 9 95.3 (±24.9) 1685 0.936 0.760
Note: DBH, diameter at breast height, represents the measured diameter of a tree at breast height, numbers in parentheses
represent standard deviations; EPS, expressed population signal, is an estimation of how well a limited chronology represents an area’s
true chronology.
1268 Can. J. For. Res. Vol. 47, 2017
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(Bunn 2008). Because WSB growth impacts are inherently autocor-
relative due to the decadal-plus temporal fingerprint of WSB out-
breaks, we chose not to remove autocorrelation from our host site
chronologies. This method of standardization ensures that dec-
adal impacts such as WSB outbreaks will be maintained, while
correcting for year-to-year age-related growth trends (Cook 1985).
Resultant ring-width indices were averaged together by tree and
used to create mean site chronologies for host and non-host sites.
A principal components analysis was run on the standard and
residual (i.e., prewhitened using autoregressive modeling) non-
host chronologies to extract the common signal shared by the
non-host trees. We chose the first principal component of our
three standard non-host master chronologies for our outbreak
reconstructions because it explained the highest shared variance
(81%) and correlated most strongly with our host chronologies.
2.4. Outbreak reconstructions
We visually compared ring-width measurements with histori-
cal USFS records of known outbreak periods within the Okanogan
Highlands (USDA Forest Service 2014), as well as nearby dendro-
chronological reconstructed outbreak dates (e.g., Campbell et al.
2006). As with crossdating, this visual comparison provided us
with a first step to identifying periods of growth suppression at
the tree level. Outbreaks are often visible as long-term growth
suppression periods in the host tree chronologies that are not
apparent in the landscape’s non-host chronology. To statistically
reconstruct outbreak records, we first subtracted climatic noise
from each host tree using the following equation:
(1) Corrected index ⫽Iht ⫺
␴
h
␴
n
(Int ⫺I
¯
n)
where I
h
is the host trees’ ring-width index for each individual
year (t), ␴
h
and ␴
n
are the standard deviations of, respectively, the
individual host tree series and the landscape-wide non-host series’
common period, I
n
is the non-host control index for each year (t),
and I
ˉ
n
is the mean for the non-host index for the common period.
The output of this equation created a new value for each year of
growth across host trees, where positive or negative values repre-
sent growth above or below the expected growth from climatic
factors alone (Nash et al. 1975;Swetnam et al. 1985). Similarities
between the corrected site indices during their shared common
periods (1719–2014 for three sites, 1796–2014 for all four) were
checked using Pearson’s correlation coefficients.
To develop an appropriate set of criteria for identifying WSB
outbreaks, we normalized the corrected tree series and identified
outbreak-length periods of low growth. We did not record non-
consecutive years of positive growth as outbreak interruptions, as
nonconsecutive positive growth years are common within out-
break periods (Swetnam et al. 1995). Minimum thresholds for WSB
outbreak length vary by region, typically ranging from 4 to 8 years
of sustained below-average growth, with at least 1 year of growth
at least 1.28 standard deviations below the long-term mean ring
width (Swetnam et al. 1995). Another defoliating insect, the
Douglas-fir tussock moth (Orgyia pseudotsugata McDunnough), can
create similar outbreak patterns in Douglas-fir ring width records,
but their outbreaks only last up to 3 years (Brubaker 1978), which
makes 4-year outbreak durations the shortest desirable outbreak
length for separating the WSB signal from similar defoliating
insects (Swetnam et al. 1995;Mason et al. 1997). We tested a min-
imum outbreak duration criterion of between 4 and 8 years
against observational outbreak records and chose 4 years as the
most reflective of historical outbreaks. A minimum growth reduc-
tion severity criterion of 1.28 standard deviations below the long-
term mean was used for all reconstructions. Outbreak periods
were identified based on these criteria for each individual tree,
resulting in an annually resolved binary record of outbreak or
non-outbreak conditions.
We standardized the binary, tree-level outbreak data into the
percentage of a site’s sample population reporting infestation
year to year. Because outbreak reconstructions tend to regularly
report some level of tree infestation reflecting endemic WSB pop-
ulations, small-scale population changes, or background noise,
we explored multiple outbreak intensity thresholds for each site
with between 30% and 80% of sampled trees reporting infestation.
We compared the resultant outbreak time series with historical
air and ground survey records (McComb 1979;Westfall and Ebata
2014;Jenkins 2015; C. Mehmel, personal correspondence, 2015)
with which a 40% threshold best identified the start of moderate
outbreak conditions. Additionally, we used thresholds of 60% and
80% to identify high and very high outbreak intensities, respec-
tively, which could gauge how intensity patterns have changed
over the entire time series for each host site. The resultant cor-
rected chronology provides measures of intensity, synchrony (the
co-occurrence of outbreaks across our sites), and duration (the
length of time when growth was below the corrected indices’
potential growth) of outbreak disturbances within and between
stands. We defined landscape-wide outbreaks as periods in which
at least two of our four sites recorded coincident outbreaks for a
minimum of two consecutive years.
2.5. Statistical analysis
2.5.1. Outbreak characteristics
We averaged outbreak duration and intensity for site and
landscape-wide outbreak records and checked for temporal
changes by dividing both duration and intensity data into two
similar-sized groups: before 1870 and after 1869. This separation
would also roughly coincide with the introduction of forestry
practices such as harvesting in the Washington Territory (Chiang
and Reese 2002). As historical records prior to 1970 either are not
reliable or do not exist for our study area, this breakpoint provides
a loose representation for when Euro-American settlers’ influ-
ences may have begun affecting regional outbreak patterns
(Johnson and Ross 2008). We conducted ANOVA on stand-level
normalized corrected indices to test for differences between
Douglas-fir’s growth response during and outside of outbreak con-
ditions. Based on the results of the Shapiro–Wilk normality test,
which indicated a non-normal distribution, we chose to use a
Kruskal–Wallis nonparametric ANOVA.
2.5.2. Outbreak synchrony among sites
We assessed the level of synchrony between stand-level out-
break histories (i.e., the percentage of each site’s trees recording
an outbreak) using Pearson’s correlation coefficients. Despite the
high autocorrelation inherent in synchrony records, which makes
estimation of statistical significance unreliable, the correlation
coefficients can be used as an approximate index of sites’ out-
break synchrony over time (Buonaccorsi et al. 2001). This simple
analysis was conducted on the percentage of each site’s sampled
trees recording outbreaks over both of our common periods (i.e.,
1719–2014 and 1796–2014).
We used a modified one-dimensional Ripley’s Kfunction (Gavin
et al. 2006) to test whether discrete outbreak events were indepen-
dent of one another over increasing bidirectional temporal lags.
Years of outbreak occurrences, initiations, and cessations for our
three oldest sites’ common period were input into K1D v1.2 soft-
ware (Gavin 2010), which returns a measure of co-occurrence (L
ˆ).
The youngest site, SMD, was removed from this method to retain
as much of our landscape’s record as possible without sacrificing
too much of our sample size (Table 1). This method checks for
co-occurrence of outbreak events between any of the sites over
increasingly long temporal windows until the bidirectional win-
dow is half of the length of the total record length, with the
resultant Kand Lfunctions providing a measure of outbreak syn-
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chrony or asynchrony over increasing temporal scales. To test for
statistical significance, we ran 1000 simulations with a 95% confi-
dence envelope using a circular randomization, with random year
data added to all site records. We also separated the 1719 common
period around the 1870 breakpoint for all three of our intensity
thresholds, i.e., moderate (40%), high (60%), and very high (80%).
This gives us a rough estimation of how site interactions may have
changed before and after major human impacts began affecting
the region.
2.5.3. Climate–outbreak associations
We conducted a Pearson’s cross-correlation analysis on both
standard and residual host and non-host chronologies against
landscape-wide instrumental and reconstructed climate records
to determine if the chronologies expressed the similar climate
responses necessary for outbreak reconstructions (Speer 2010).
Our climate records included both historical (1895–2014; National
Oceanic and Atmospheric Administration (NOAA) 2015) and re-
constructed (1685–2003; Cook et al. 2004) Palmer drought severity
indices (PDSI; Palmer 1965). PDSI records provide a measure of
summer (i.e., between June and August) moisture stress based on
soil type, precipitation, and temperature (Palmer 1965). Cook
et al.’s (2004) multicentury, gridded PDSI reconstruction network
is available for 2.5° × 2.5° grid cells, with our landscape’s data
drawn from grid 43 (Cook et al. 2004). In addition to PDSI data, we
used historical precipitation data for water years (i.e., previous
October to current September) and growing years (April to Sep-
tember of the current year) for the Okanogan Big Bend (Climate
Division 7) area (NOAA 2015).
To identify climatic conditions associated with WSB outbreak
initiations and cessations, we used superposed epoch analysis to
identify patterns of climatic conditions associated with outbreak
initiation and cessation dates. Superposed epoch analysis uses
event years (i.e., outbreak initiation and cessation dates) with time
series data and designated temporal lags to test for significant
departures from the mean (Grissino-Mayer 2001). We defined
initiation dates as the first of two or more consecutive outbreak
years following a gap of at least 2 years without recorded out-
breaks and cessation dates as the first of at least 3 years of
non-outbreak conditions following an outbreak. However, we ac-
knowledge that these dates are approximate, as there may be a lag
of up to 3 years between the actual date of outbreak initiations or
cessations and the onset of resulting radial growth impacts
(Alfaro et al. 1982). We quantified climate anomalies using both
historical and reconstructed climate records for an 11-year win-
dow centered on outbreak events. Statistical significance was as-
sessed with 1000 Monte Carlo simulations using dplR (Bunn 2008).
To assess longer term patterns of climate associated with out-
breaks, we conducted paired, two-sample ttests to test for differ-
ences between PDSI data associated with outbreak conditions
against non-outbreak conditions.
3. Results
3.1. Dendrochronological characteristics and outbreak
histories
A total of 69 host trees and 32 non-host trees were sampled over
our six sites. Our landscape-wide non-host chronology dated to
1685. Host site records with at least two trees started between 1685
and 1796 (Table 1). Interseries correlation (Pearson’s r;p< 0.01 for
all pairs) for our host sites ranged between 0.650 and 0.780, while
non-host sites ranged between 0.627 and 0.760. Correlation coef-
ficients (Pearson’s r) between both our host and non-host chronol-
ogies and climate data supported the use of our sites for outbreak
reconstructions (Table 2). All of our host site residual chronolo-
gies, as well as our landscape-wide residual non-host chronology,
reported significant (p< 0.05), positive relationships with recon-
structed and historical PDSI, as well as water-year precipitation
for the current and preceding year. The relationship with temper-
ature returned less significance, although the average July tem-
perature had a significant, negative relationship with all but our
non-host chronology (Table 2).
Outbreak durations, based on sites with at least 40% of their
sampled trees reporting outbreak conditions, ranged from 2 to
19 years across sites, with mean site-level outbreak durations
ranging between 8.6 (±3.9) and 10.7 (±5.8) years by site (Table 3).
Quiescent periods lasted between 4 and 52 years, with site means
ranging between 11.4 (±7.5) and 20.0 (±10.1) years. The average
for the landscape-wide outbreak duration and quiescent period
length was 8.3 (±4.3) and 13.3 (±11.0) years, respectively. The
Kruskal–Wallis ANOVA analysis suggested stand-level corrected
indices during and between outbreaks are significantly different
(Table 3). All four of our sites showed changes between the early
(1685–1869) and modern (1870–2014) periods, with more years re-
porting outbreaks in the modern period.
3.2. Intersite outbreak synchrony
During the 330 years covered by our landscape-wide reconstruc-
tion (1685–2014), all reporting sites experienced identical out-
break conditions (either outbreak or non-outbreak) during 184
individual years (55.8% of years in the common period). There was
a total of 16 landscape-wide outbreaks (i.e., periods in which at
least two sites shared concurrent outbreak conditions) covering
130 years (39.4%) of the total 330 years. Outbreak and non-
outbreak conditions tended to occur synchronously or near syn-
chronously (Fig. 2), with synchrony increasing after 1869. Using
our moderate intensity threshold, the early period included 43.8%
of landscape-wide outbreak years (i.e., years with outbreaks at two
or more sites), and the modern period included 56.2%. Based on
the moderate outbreak threshold, there has been little to no
change in outbreak synchrony since the start of the reconstruc-
tion. However, analysis using higher intensity thresholds revealed
an increase in high-intensity, synchronous outbreaks in the mod-
Table 2. Cross-correlation (Pearson’s r;p< 0.05 except where noted) values of residual host (Douglas-
fir) chronologies and the landscape’s non-host (ponderosa pine) chronology against reconstructed
(1685–2003) and historical (1895–2014) climate data for the Okanogan Highlands.
Site
a
PDSI
(Cook)
PDSI
(NOAA) WYP
Previous
year’s WYP GYT
Previous
year’s GYT
Mean July
temperature
MPD 0.40 0.39 0.37 0.24 –0.08
b
–0.06
b
–0.22
SMD 0.42 0.48 0.42 0.29 –0.13
b
–0.06
b
–0.18
TMD 0.33 0.27 0.22 0.33 –0.36
b
–0.13
b
–0.22
VLD 0.47 0.46 0.40 0.27 –0.13
b
–0.03
b
–0.24
Landscape non-host 0.56 0.53 0.53 0.28 –0.09
b
–0.11
b
–0.12
b
Note: PDSI, summer (June to August) Palmer drought severity index, provided either by Cook et al. (2004) as
climate reconstructions (1685–2003) or NOAA’s historical records (1895 –2014); WYP, water-year (previous October to
current September) precipitation; GYT, growing-year (April to September) temperature.
a
Host sites Mount Phoebe (MPD) and Tunk Mountain (TMD) reflect the full reconstructed PDSI record (1685–2003).
Sneed Mountain (SMD) covers only 1796–2003, and Virginia-Lily (VLD) covers 1719–2003.
b
Value does not represent a significant (p< 0.05) relationship.
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ern period (Table 4). Using our very high intensity threshold, all
landscape-wide synchronous outbreaks occurred after 1869 (1938,
1992, and 2010). For our three oldest sites, very high intensity
outbreaks occurred in 0% to 5.9% of the total early period years
and between 6.9% and 14.5% of the modern period years.
Pearson’s correlation of outbreak histories also revealed a pat-
tern of synchrony. The average intersite correlation for outbreak
histories for the three oldest sites (i.e., MPD, TMD, and VLD) was
0.60, while all four sites yielded a correlation of 0.71. The Tunk
Mountain Douglas-fir (TMD) reduces correlations of both periods,
likely due to a unique period of asynchronous, stand-specific out-
breaks during the mid-19th century also recorded in nearby out-
break reconstructions (Fig. 2;Campbell et al. 2006;Axelson et al.
2015).
The modified one-dimensional Kstatistic for all outbreak years
was statistically significant (p< 0.05) for up to 11 years for our
three sites dating to 1719 (Fig. 3). Initiation and cessation dates for
the 1719 common period showed significant temporal synchrony
over windows up to 6 and 9 years, respectively, with a higher
degree of synchrony for initiation events than cessation dates or
all outbreak years (Fig. 4). In the early period (1719–1869), no sig-
nificant synchrony was found for outbreaks using our high and
very high outbreak intensities (Fig. 3). All outbreak intensities
reported up to 9 to 24 years of synchrony for the late period
records (1870–2014).
3.3. Climatic influences on outbreaks
Outbreak initiation dates were preceded by between 2 and
5 warm–dry years at all sites, with initiation dates tending to occur
in cooler, wetter years (Fig. 5). While no site reported statistically
significant cool–wet years in the 5 years following an initiation
event, all sites still showed a shift towards cool–wet conditions.
Our landscape-scale outbreak record (1685–2014) shows a statisti-
cally significant warm–dry anomaly in the second year preceding
initiation events (Fig. 6). Paired, two-sample ttests revealed signif-
Table 3. Outbreak statistics for our four Douglas-fir host sites (MPD, SMD, TMD, and VLD) and our
landscape-wide outbreak record in the Okanogan Highlands.
Site
a
No. of
outbreaks
Mean outbreak
length (years)
Mean quiescent
period (years)
b
% of record
with outbreak
conditions
Outbreak and
non-outbreak
ANOVA
c
MPD 15 8.6 (±3.9) 14.5 (±11.4) 38.2 97.85, p< 0.01
SMD 8 9.1 (±4.5) 20.0 (±10.1) 32.4 67.24, p< 0.01
TMD 17 8.9 (±4.3) 11.4 (±7.5) 44.6 109.85, p< 0.01
VLD 11 10.7 (±5.8) 16.0 (±13.6) 38.2 83.67, p< 0.01
Landscape-wide
d
16 8.3 (±4.3) 13.3 (±11.0) 39.4 112.24, p< 0.01
Note: Numbers in parentheses represent standard deviation.
a
Host sites: MPD, Mount Phoebe; SMD, Sneed Mountain; TMD, Tunk Mountain; VLD, Virginia-Lily.
b
Mean quiescent period represents the average period of time between outbreak cessations and subsequent
outbreak initiations.
c
Kruskal–Wallis ANOVA conducted on corrected indices during outbreak conditions against non-outbreak con-
ditions, expressed as ␹
2
and pvalues, respectively.
d
Landscape-wide outbreak record represents times when two or more sites reported concurrent outbreaks
(1685–2014).
Fig. 2. Percentage of trees recording an outbreak at our four
Douglas-fir host sites. Solid black lines represent an 8-year moving
average of the percentage of trees returning outbreak records, and
the dashed line represents the unfiltered outbreak records. The two
dotted straight lines indicate two of our outbreak intensity levels
wherein our sites have at least 40% (moderate) and 80% (very high)
of the sampled trees reporting outbreak conditions.
Table 4. Percentage of outbreak years occurring in the early (1685–
1869) and late (1870–2014) periods using moderate (40% of trees),
high (60% of trees), and very high (80% of trees) outbreak intensity
thresholds.
Site
Moderate High Very high
Early Late Early Late Early Late
MPD 34.1 43.4 21.6 23.4 5.9 14.5
SMD 20.3 38.6 8.1 22.1 0.0 6.9
TMD 41.6 48.3 6.5 26.9 2.2 11.7
VLD 33.8 42.8 13.9 22.1 2.6 13.1
Landscape-wide 30.8 50.3 9.7 28.3 0.0 14.5
Note: Mount Phoebe (MPD), Sneed Mountain (SMD), Tunk Mountain (TMD),
and Virginia-Lily (VLD) represent our four Douglas-fir host sites in the Okanogan
Highlands, and the landscape-wide record represents time when two or more
sites reported outbreak conditions (1685–2014). Percentages shown are the total
number of years within each period’s length. SMD (1796–2014) and VLD (1719 –2014)
do not represent equal measures of time between early and modern periods.
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icantly (t= 2.83, p= 0.01) cooler, wetter conditions during outbreak
years (mean PDSI = 0.51) than during non-outbreak years (mean
PDSI = –0.26).
We identified a tendency for shifts from cool–wet to warm–dry
conditions during outbreak cessation years (Fig. 5). Between three
and four sites reported cool–wet conditions in each of the 5 years
preceding outbreak cessation dates, with two sites reporting at
least one significant year of cool–wet conditions. The landscape-
wide outbreak record shows the same pattern, with cool–wet con-
ditions shifting to warm–dry conditions 1 year prior to cessation
dates.
We saw the same patterns for historical PDSI data (1895–2014)
from climate station records (Fig. 5). All sites reported warm–dry
conditions for at least 3 years preceding outbreak initiations, with
one site reporting significance for 3 years. Following outbreak
initiations, all sites reported cool–wet periods for at least 2 years,
with three sites reporting significant cool–wet conditions. Three
sites reported warm–dry conditions during outbreak initiation
events. All sites reported warm–dry conditions at least once in the
2 years following outbreak initiations, with one instance of signif-
icance. The landscape-wide outbreak record exhibits a statistically
significant pattern of warm–dry conditions 2 years prior to initi-
ation events, with significant cool–wet periods between 3 and
5 years after initiation dates (Fig. 6). All four of our sites and the
landscape-wide outbreak record showed between 1 and 4 signifi-
cant years of cool–wet conditions prior to cessation dates using
the historical PDSI data, with no sites returning significant condi-
tions following cessation dates (Fig. 6).
4. Discussion
4.1. Outbreak histories
We were able to successfully reconstruct 330 years of WSB out-
break history for the Okanogan Highlands. Our reconstructed
outbreak dates closely match those recorded in historical docu-
ments and aerial survey reports. Because accurate historical re-
cords for our study area are only available after the 1970s, nearby
historical records for southern B.C. were used alongside our land-
scape’s records to check against our outbreak reconstructions.
Harris et al. (1985) used historical records to identify WSB out-
breaks as hectares affected, percentage of trees infested, or sever-
ity of impact (e.g., existence of topkill) in the Canadian Cascade
Range for the 1923–1930, 1943–1958, and 1977–1983 periods, with
all but the earliest outbreak period not reflected in our data. WSB
defoliation and population data were not recorded for the region
between 1931 and 1942, possibly explaining the discrepancy be-
tween our reconstructions and historical records. The three most
recent outbreaks (1975–1983, 1990–2001, 2009–present) concur
with the USFS insect survey data and other WSB outbreak studies
from the Pacific Northwest (USDA Forest Service 1977,2014;
Fig. 3. Modified Ripley’s Kfunction (L
ˆ) calculated for all outbreak years (1719–2014) in the Okanogan Highlands using moderate (40% of
sampled trees reporting outbreak conditions), high (60%), and very high (80%) outbreak intensities. The top row represents all years of data.
The middle and bottom rows separate the outbreak years between early (1719–1869) and late (1870–2014) periods. Note the change to the yaxis
due to the decreased sample sizes for very high intensity outbreaks.
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McComb 1979;Alfaro et al. 2014;Axelson et al. 2015). Some incon-
sistencies between aerial survey records and our reconstructed
outbreak dates may be due in part to inconsistent quality control
and accuracy in identifying insect outbreaks via aerial survey
(Johnson and Ross 2008).
Climate–growth analysis showed that the annual radial growth
rates of both host and non-host trees were significantly limited by
moisture stress (Table 2). Similar to Chen et al. (2010), we found
positive correlation between our trees’ radial growth and precip-
itation values, as well as negative correlation with temperature
values. This suggests that warm–dry conditions inhibit radial
growth rates similarly in both ponderosa pine and Douglas-fir,
while cool–wet conditions promote radial growth rates. The sim-
ilarity in the climate–growth responses of the two species sup-
ports our use of ponderosa pine as a proxy for climatic variability
in the construction of our corrected indices.
Douglas-fir dwarf mistletoe (Arceuthobium douglasii Engelm.) was
prevalent in 11 of our sampled trees from MPD and VLD, but no
associated radial growth anomaly could be identified (Hadfield
et al. 2000). External signs of severe Douglas-fir dwarf mistletoe
infection are known to overlap with signs of long-term WSB in-
festation, but radial growth impacts are unrelated (Hadfield et al.
2000). The 1975–1983 landscape-wide outbreak shows no lag be-
tween our reconstruction and historical records for the initiation
year, which may be the result of signal contamination by Douglas-
fir tussock moth’s landscape-wide 1970–1974 outbreak (C. Mehmel,
personal correspondence, 2014). The Douglas-fir tussock moth im-
pacts trees’ growth response similarly to the WSB, which could
replace the lag between outbreak initiation and trees’ growth
response that we expect to see with WSB outbreaks (Brubaker
1978). Such overlaps are rare but always a potential issue with
WSB studies, and this is the only known case in our study site of
Douglas-fir tussock moth and WSB outbreak records overlapping.
Because the relationship between our reconstructed outbreak his-
tory and moisture availability follows other studies (e.g., Swetnam
and Lynch 1993;Flower et al. 2014a), we can safely assume the
Douglas-fir tussock moth’s influence on our reconstructions is
minimal, but we acknowledge that a more conservative interpre-
tation of our record would be that this is a history of defoliation
events in general.
Our outbreak reconstructions resulted in outbreak patterns
similar to those seen in nearby regions. The landscape’s average
outbreak duration of 8.3 years roughly matches nearby studies in
the Pacific Northwest (Campbell et al. 2006, 12 years; Flower et al.
2014a, 12 years; Alfaro et al. 2014, 7 years; Axelson et al. 2015,
11.2 years), while the landscape’s quiescent period of 13.3 years
was the lowest among nearby studies, which ranged between 15 to
64.2 years.
4.2. Intersite outbreak synchrony and driving factors
Our reconstructions show that WSB outbreaks have been occur-
ring synchronously in the region back to at least 1685. The
landscape-wide outbreak records showed 16 instances of synchro-
nous outbreaks occurring between 1685 and 2014. Similar to other
studies, our region has seen an increase in outbreak synchrony
but not duration or frequency after the 19th century (Ryerson
et al. 2003;Alfaro et al. 2014). The increase in outbreak synchrony
is likely related to anthropogenic climate change and changing
land-use regimes. Climate change over the 20th century has pro-
moted climatic variability and aridity (Cook et al. 2004), with
warming temperatures, regardless of changes to moisture avail-
ability, effecting an increase in the moisture stress response of
trees during summer months (Coops and Waring 2011). Changing
land-use regimes have increased forest homogenization by favor-
ing expansion and increased density of the WSB’s host tree species
through practices such as fire exclusion and logging (Swetnam
and Lynch 1993;Wickman 1992;Swetnam et al. 1995;Hessburg
et al. 1994;Keane et al. 2002;Maclauchlan and Brooks 2009).
At our sites, a highly asynchronous period of site-specific out-
breaks occurred between 1820 and 1870 during which only one
site (TMD) was impacted by outbreaks. This asynchronous period
is also reported by nearby records (Harris et al. 1985;Campbell
et al. 2006;Axelson et al. 2015) and may be at least partially attrib-
utable to alternating regimes of warm and cool sea surface temper-
atures driven by the Pacific Decadal Oscillation teleconnections
between 1840 and 1923 affecting local climate variables such as PDSI
(Gedalof and Smith 2001;Campbell et al. 2006).
Higher intensity outbreaks at both site and landscape levels
were more frequent in the last century than in previous centuries.
The degree of synchrony tended to increase with the intensity
threshold used, particularly when looking at outbreaks that oc-
curred during the late period (1870–2014). This clustering of syn-
chronous events towards the 20th century suggests that the
patterns of synchrony that we see in the full records (i.e., 1719–
2014) for high and very high intensities may not accurately reflect
the clustered pattern due to the method of randomization built
into the K1D software being less effective at finding patterns with
increasingly clustered temporal events (D. Gavin, personal com-
munication, 2016). The highest tested intensity threshold had no
landscape-wide outbreak events prior to the 20th century, making
the degree of frequency and synchrony in the late period unprec-
edented. Three landscape-wide outbreaks of very high intensity
occurred among our sites and all of them in the last century
(during the 1940s, 1990s, and 2010s), strongly suggesting that an-
thropogenic impacts such as climate change or land-use practices
play a primary role.
The drivers of synchronous insect outbreaks are not fully un-
derstood, but there is support for the role of both fine-scale (i.e.,
up to 200 km, but strongest up to 100 km) dispersal abilities and
exogenous, abiotic stochastic factors in driving WSB and similar
insect outbreak synchrony (Peltonen et al. 2002;Liebhold et al.
Fig. 4. Modified Ripley’s Kfunction (L
ˆ) for moderate outbreak
initiation dates and cessation dates. All dates were taken from our
three host Douglas-fir sites dating to 1719 to include as much of the
record with as many of our sites as we could. The yaxis represents a
level of synchrony (positive) or asynchrony (negative) calculated
using the temporal window (1 to 30 years) shown on the xaxis, with
the shaded region representing the confidence interval (95%).
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2004). WSB and similar moths have been found capable of flying
hundreds of kilometres in above-canopy winds (Greenbank et al.
1980;Campbell 1993), and synchrony of outbreak records is high-
est among sites less than 100–200 km apart (Peltonen et al. 2002),
suggesting a moderate dispersal ability constrained by geography
such as mountainous terrain. Because our sites were all within
50 km of one another, it could be assumed that dispersal plays a
role in our outbreak synchrony. Dispersal abilities are likely in-
fluenced by local land-use histories, as well, which have promoted
the expansion and growth of Douglas-fir over non-host species
such as ponderosa pine since the late 19th century. Coupled with
fire exclusion, this has led to an increase in host range and canopy
density (Swetnam and Lynch 1993;Maclauchlan and Brooks 2009).
This homogenization of host forests could also increase dispersal
abilities over smaller areas with limited topographic barriers such
as the Okanogan Highlands, potentially leading to higher popula-
tion densities during outbreak conditions (Willhite and Stock
1983). Another potential factor, the influence of trophic interac-
tions on WSB populations, has been underexplored in research
but is assumed as similarly limited to local area due to the mobility of
insectivores nearly mirroring prey dispersal abilities (Peltonen et al.
2002).
The Moran theorem proposes that the spatial and temporal
autocorrelations of abiotic, exogenous factors help to synchronize
biotic populations over a landscape (Moran 1953). Regional cli-
matic stochasticity has been found to be the dominant influence
synchronizing many insect species’ population dynamics, partic-
ularly over larger spatial scales (Peltonen et al. 2002;Swetnam and
Fig. 5. Summary of superposed epoch analysis summary of our four host Douglas-fir sites’ initiation (first year of outbreak) and cessation
(first year of non-outbreak conditions following an outbreak) dates using Cook et al.’s (2004) PDSI reconstructions (1685–2003) and historical
(1895–2014; NOAA 2015) PDSI records. Ascending bars represent number of sites with positive PDSI anomaly; descending bars represent
number of sites with a negative PDSI anomaly. Instances of high significance are noted by dark grey (90%) and black (95%) shading.
Fig. 6. Superposed epoch analysis using the landscape-wide outbreak initiation and cessation dates for the Okanogan Highlands. We used
Cook et al.’s (2004) PDSI reconstructions (1685–2003) and historical (1895–2014; NOAA 2015) PDSI records. Ascending and descending bars
represent positive and negative departures from the mean, respectively. Instances of high significance (95%) are noted by black shading.
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Lynch 1993;Flower et al. 2014a). Flower (2016) linked widespread
synchrony of WSB outbreaks with fluctuations in moisture avail-
ability. Synchrony across the scale of the landscape that we ana-
lyzed could be due to dispersal or climatic controls or, most likely,
a combination of the two. However, our outbreak history is strik-
ingly similar to outbreak records at other sites across much of
western North America. We found that all our outbreak records
between 1700 and 1990 coincide with synchronous outbreaks re-
corded in three to six other regions (central B.C., southern Colo-
rado, northern New Mexico, Idaho, Oregon, and (or) Montana).
Specifically, the landscape-wide outbreaks that occurred during
1715–1717, 1742–1752, 1760–1768, 1775–1777, 1785–1797, 1809–1814,
1819–1829, 1871–1883, 1892–1898, 1901–1910, 1938–1956, 1960–
1963, and 1975–1983 all fall within time periods of widespread,
synchronous outbreaks (Flower 2016). This scale of synchrony sug-
gests that climate, which varies over a similarly large geographic
scale, plays a role in the synchronization of WSB outbreaks.
4.3. Outbreaks and climatic variability
WSB outbreak initiation dates show a distinct trend of transi-
tioning climate from warm–dry conditions to cool–wet condi-
tions: all four of our sites showed strong warm–dry conditions in
two or more years immediately prior to initiation events (Fig. 5).
During and after initiation dates, climate tended towards cool–
wet conditions. This pattern of cool–wet climate conditions during
outbreak conditions has been identified by other dendrochrono-
logical studies (Swetnam and Lynch 1993;Swetnam et al. 1995;
Ryerson et al. 2003;Flower et al. 2014a). Because a variable lag of
1 to 3 years for both initiation and cessation dates usually exists
between the actual time of an infestation’s initiation or cessation
and impact on a tree’s radial growth (Alfaro et al. 1982;Swetnam
et al. 1995;Mason et al. 1997), this suggests that the warm–dry years
prior to an outbreak initiation represent the climatic conditions
driving WSB outbreak initiations, and the subsequent transition
to cool–wet conditions are necessary to sustain outbreak-level pop-
ulations. This is consistent with previous studies that linked
warm–dry conditions to outbreak initiation timing (Hard et al.
1980;Thomson et al. 1984;Campbell 1993;Flower et al. 2014a).
The transitional climate conditions that we found associated
with outbreak initiations supports the nonlinear pulsed plant
stress hypothesis (Huberty and Denno 2004;Mody et al. 2009)in
which temporal variability in moisture stress was proposed as
crucial for initiating and subsequently sustaining insect out-
breaks. Moderate drought stress has been found to favor WSB and
similar herbivorous insects’ growth and reproductive rates, as
well as larval survival, by increasing foliar concentrations of ni-
trogen, sugars, and other favorable compounds (Mattson and
Haack 1987;Campbell 1993). These changes to foliage composition
prior to transitioning climate conditions would benefit the growth
and survival of WSB during larval stages by favoring the species’
diet during moderate drought stress and subsequently allowing
for increased needle production and decreased needle toughness
during sustained cool–wet conditions (Gower et al. 1992). This
relationship can, however, reverse with prolonged outbreak con-
ditions or increasing outbreak severity (Mattson and Haack 1987;
Campbell 1993;Huberty and Denno 2004). Our results indicate the
nonlinear relationships described by the pulsed plant hypothesis
as the strongest explanation for WSB outbreak dynamics over
multicentury records.
As with initiation dates, cessation dates are expected to show a
1- to 3-year lag between years of outbreak conditions and a tree’s
return to normal growth conditions during the recorded cessa-
tion date (Swetnam et al. 1995;Mason et al. 1997). This suggests
that the 5 years of sustained cool–wet conditions recorded at our
sites should represent the conditions in which outbreak-level
WSB populations crashed (Fig. 5). Cessation dates with defoliating
species such as WSB are typically attributed to a loss of food from
sustained overpopulation and trophic interactions with natural
predators, parasites, or pathogens (Nealis 2016). As available nee-
dles become more sparse or difficult to mine, the WSB population
density inevitably dips, while predators, parasitoids, and patho-
gens that prey on WSB are able to maintain population densities
and increasingly contribute to WSB population losses (Nealis
2016). Despite also showing a transitioning climate around cessa-
tion dates, the transition to warm–dry conditions after cessation
would not have a causal relationship with the WSB’s population
crashes. However, because our superposed epoch analysis consis-
tently reported cool–wet conditions at three to four of our sites
over 5 years prior to cessation dates, it is likely that long-term
maintenance of cool–wet conditions plays a role in WSB popula-
tion crashes via climatic effects on trophic interactions, food loss,
emergence and budburst timing, and physically damaging local
weather conditions (Fellin and Dewey 1982;Campbell 1993).
5. Conclusion
WSB outbreaks have been occurring synchronously in the
Okanogan Highlands since at least 1685. Outbreak synchrony
across the landscape has increased in the late period (1870–2014).
Although moderate-intensity outbreaks only increased in syn-
chrony, high-intensity and very high intensity outbreaks saw dras-
tic increases in both frequency and synchrony between the early
(pre-1870) and late (post-1869) periods. It is probable that these
changes were influenced by changing land-use regimes initiated
by western expansion in the 19th century, with impacts such as
forest homogenization and fire exclusion favoring the expansion
of WSB’s host species and thus increasing the likelihood of fre-
quent, widespread WSB outbreaks.
Our superposed epoch analyses found strong relationships be-
tween landscape- and site-level outbreak histories and moisture
availability using both dendroclimatic and observational climate
records. Outbreak initiation dates showed a relationship with
multiple, consecutive years of low moisture availability in the
years preceding initiation events and consecutive years of high
moisture availability during and after initiation years. Cessation
dates, on the other hand, showed a strong relationship with high
moisture availability during the 5 years preceding recorded cessa-
tion dates. The temporal variability in moisture availability occur-
ring during and around outbreak events supports the pulsed plant
stress hypothesis in explaining WSB outbreak dynamics: high
moisture stress encourages increases in WSB populations and dis-
persal rates and a shift to low moisture stress is necessary to
maintain the inflated outbreak-level populations.
The results of our study suggest that a complex combination of
climate change, land-use patterns, and disturbances such as fires
will continue affecting WSB outbreak dynamics in coming centu-
ries, and continued study is needed to better understand how this
complex interplay of exogenous factors will direct WSB popula-
tions. Regional and global climate models project a continuing
rise in temperatures over the 21st century, while precipitation
may be impacted by stronger seasonality, including drier sum-
mers (Mote and Salathé 2010). These projected changes will likely
increase the frequency of drought conditions necessary for initi-
ating WSB outbreaks. It is also possible that the increase in
drought conditions could hamper WSB outbreaks if drought con-
ditions are sustained over too many consecutive years or occur too
frequently, as the climatic reversal of warm–dry to consecutive
cool–wet conditions appears necessary in sustaining outbreak-
level WSB populations. Changes to land-use practices over the
next century should also impact the occurrence of WSB out-
breaks. A potential increase in forest fire occurrences with a
changing climate could lead to changes in the landscape’s bio-
mass available to WSB populations, leading to indirect effects on
WSB dynamics (Flower et al. 2014b). Additionally, changing cli-
mate may drive shifts in the distribution of the WSB’s host popu-
lations over coming centuries.
Ellis and Flower 1275
Published by NRC Research Press
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xppws S⫽3 8/8/17 11:51 Art: cjfr-2016-0399 Input-1st disk, 2nd ??

Acknowledgements
We would like to thank Paul Nash of the USFS for his assistance
in locating study sites essential for our study. We are also grateful
to Connie Mehmel of the USFS for her knowledge of the study
area’s management history. Daniel Gavin of the University of
Oregon also provided important feedback on our statistical
methods. Andy Bunn and Michael Medler of Western Washington
University provided important feedback and guidance during the
course of the project. Lastly, this project would not have been
possible without the field and lab assistance of Marissa Bhatnagar,
Branden Rishel, Christopher Zemp, Venice Wong, Ryan Schum-
acher, Shelby Van Arnam, Demian Estrada, Derek Huling, and
Dustin Gleaves.
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