Incidence and Severity of Swiss Needle Cast in the Coastal Forest of Western Washington: Examining Climactic Correlation

Item

Title

Eng Incidence and Severity of Swiss Needle Cast in the Coastal Forest of Western Washington: Examining Climactic Correlation

Date

2016

Creator

Eng Boderck, Michele

Subject

Eng Environmental Studies

extracted text

INCIDENCE AND SEVERITY OF SWISS NEEDLE CAST
IN THE COASTAL FOREST OF WESTERN WASHINGTON:
EXAMINING CLIMATIC CORRELATION

by
Michele Boderck

A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
June 2016

© 2016 by Michele Boderck. All rights reserved.

This Thesis for the Master of Environmental Studies Degree
by
Michele Boderck

has been approved for
The Evergreen State College
by

________________________
Richard Bigley, Ph.D.
Member of the Faculty

________________________
Date

ABSTRACT
Incidence and Severity of Swiss Needle Cast in the Coast Forest of Western Washington:
Examining Climatic Correlation
Michele Boderck
The Pacific Northwest (PNW) is experiencing an epidemic of Swiss needle cast
(SNC), a foliage disease that affects Douglas-fir exclusively and is caused by the fungus,
Phaeocryptopus gaeumannii. Symptoms include chlorotic (yellow) needles, decreased
foliage retention, and reductions in growth. Although tree mortality is rare, because there
are few tools to combat SNC other than tree species substitution, the epidemic is a major
concern for the region’s timber industry, economy, and general forest health. SNC is
native to the PNW, but emerged as an epidemic in coastal Washington and Oregon in the
1970s and has steadily increased since then. The causes are not entirely understood,
however, the extensive planting of Douglas-fir stands in the coastal forest where this
species is naturally rare, as well as the warm, wet climate of the coast that is conducive to
fungal growth, are likely contributing factors. This research sought to answer the
questions of: What is the incidence and severity of SNC in western Washington? What
climate variables are most correlated with its growth? Needle samples were collected in
the spring of 2015 from 47 sites throughout western Washington and examined for
pseudothecia (fungal fruiting body) abundance. Results indicated a colonization index of
5.3 for one-year-old needles and 22.5 for two-year-old needles. This demonstrates an
increase in disease severity from ground surveys conducted in 2011 and 2012.
Additionally, correlations between colonization indices and various climate variables
calculated with Climate WNA software at the monthly, seasonal, and annual scale were
examined using a linear regression analysis. No correlation between climate and disease
severity was found in this study, however, literature suggests that climate is playing some
role in disease severity: other factors may be making the relationship less clear in this
study. Due to the effects that growth loss from SNC can have on the economy of
Washington State and forest health in general, further research into the cause of SNC
spread and how climate conditions affect the disease are recommended.

Table of Contents
CHAPTER I: Literature Review ..................................................................................................... 1
Introduction .................................................................................................................................. 1
Significance of Douglas-fir in the Pacific Northwest .................................................................. 2
What is Swiss needle cast?........................................................................................................... 4
The life cycle of P. gaeumannii ............................................................................................... 4
Effects on Douglas-fir .............................................................................................................. 6
History of Swiss needle cast discovery ...................................................................................... 11
Worldwide spread followed by discovery in United States ................................................... 11
A worsening epidemic ........................................................................................................... 12
Investigating the cause of the epidemic ................................................................................. 14
Current research ......................................................................................................................... 19
Attempts to control/minimize disease impacts ...................................................................... 19
Increasing our understanding of the disease: the importance of monitoring surveys ............ 24
Identifying favorable conditions ............................................................................................ 28
Lack of environmental condition analysis in Washington ..................................................... 33
Conclusion ................................................................................................................................. 35
CHAPTER II. Manuscript ............................................................................................................ 37
Introduction ................................................................................................................................ 37
Viewing the epidemic as a pathologist .................................................................................. 38
Searching for climate correlations ......................................................................................... 41
Methods...................................................................................................................................... 42
Field assessments ................................................................................................................... 42
Quantifying SNC severity ...................................................................................................... 46
Climate Data .......................................................................................................................... 47
Statistical Analysis ................................................................................................................. 50
Results ........................................................................................................................................ 51
Direct quantification of SNC severity .................................................................................... 51
Testing for correlation between disease severity and climate ................................................ 57
Discussion .................................................................................................................................. 62
Direct quantification of SNC severity .................................................................................... 62
Testing for correlation between disease severity and climate ................................................ 64
Conclusion ................................................................................................................................. 66

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v

List of Figures
Figure 1. Images of pseudothecia .................................................................................................. 5
Figure 2. Washington aerial survey maps showing the spread of SNC from 2012 to 2015 ........ 13
Figure 3. Area of western Oregon showing SNC during aerial surveys in 1996-2014 ................ 14
Figure 4. Map of Sitka spruce vegetation zone ............................................................................ 18
Figure 5. Healthy Douglas-fir compared to one showing decreased needle retention ................. 25
Figure 6. The disease triangle of the interaction between pathogen, environment, and host ........ 39
Figure 7. Map of 2015 ground survey sites in western Washington ............................................ 43
Figure 8. Layout of the 75 m transect used at each site for sampling .......................................... 44
Figure 9. Location of branch sampled.......................................................................................... 46
Figure 10. Microscopic view of pseudothecia on the underside of a Douglas-fir needle ............ 47
Figure 11. SNC colonization index by site sampled in the spring of 2015 in western WA ......... 52
Figure 12. Distribution of normalized colonization index for one- and two-year-old needles ..... 53
Figure 13. The trend in colonization index over the years of ground surveying in Washington .. 54
Figure 14. Variation in site severity across the 19 sites sampled during all three surveys ........... 55
Figure 15. Ranking of site severity over the three years of surveying in Washington ................. 56
Figure 16. Map of 2015 ground survey sites over Sitka spruce forest zone ................................. 57
Figure 17. Relationship between colonization index and average winter temperature ................ 59
Figure 18. Relationship between actual and predicted colonization index ................................... 60
Figure 19. 2012 ground survey sites categorized by colonization index level.............................. 61
Figure 20. Relationship between colonization index and winter temperature in NZ, OR ............ 65

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List of Tables
Table 1. ClimateWNA variables tested for correlation with disease severity .............................. 49
Table 2. Summary statistics of colonization index for one-year-old needles................................ 53
Table 3. Summary statistics of colonization index for two-year-old needles ............................... 54
Table 4. Pearson correlation coefficients between CI and seasonal climate variables ................. 58

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Acknowledgements
I would first like to thank my reader, Richard Bigley, who willingly stepped into
this role mid-process and was an incredible mentor throughout my two years at
Evergreen. I would also like to thank the other MES faculty, particularly Erin Martin and
Peter Dorman for advising me throughout various other stages and providing their insight
and expertise. The forest pathologists at the Washington Department of Natural
Resources, Dan Omdal and Amy Ramsey, were kind enough to include me in their Swiss
needle cast surveying, providing me with the basis of my research. Jeff Stone and Tongli
Wang were also generous in their capacity as external advisors. I would also like to
thank Patrick Ferguson for graciously volunteering to edit my writing. Finally, thank you
to my friends, family, and MES cohort for all your support; you are what made a good
two years great.

viii

CHAPTER I: Literature Review
Introduction
Swiss needle cast (SNC) is a foliage disease caused by the pathogenic fungus,
Phaeocryptopus gaeumannii that exclusively infects Douglas-fir (Pseudotsuga
menziesii). While SNC is not usually directly linked to tree mortality, symptoms include
chlorosis (yellowing of foliage), decreased needle retention, and most importantly,
above- and below-ground growth loss. The fungus is believed to be endemic to the
Pacific Northwest (PNW) and ubiquitous across the native range of Douglas-fir in
western North America (Boyce 1940) but for reasons not entirely clear, an epidemic has
emerged over the last thirty years on the outer coast of Washington and Oregon.
Considering the importance of the timber industry, and thus Douglas-fir, to the Pacific
Northwest, this disease has turned into an important coastal forest health issue.
This literature review will discuss the importance of Douglas-fir to the Pacific
Northwest timber industry and thus Washington State’s economy. An explanation of the
SNC disease will follow, covering the life cycle of the causal fungus, its effects on
Douglas-fir, and the spread and possible causes of the current epidemic. Current research
into attempts to minimize disease impacts, methods for monitoring, and favorable
environmental conditions is reviewed. The lack of an environmental analysis in
Washington is identified as a key gap in the literature, prompting this study. Due to the
nature of the disease varying geographically, learning which conditions are most
correlated with disease severity in western Washington will advance our understanding of
SNC and potentially enable us to inform landowners of high-risk areas.

1

Significance of Douglas-fir in the Pacific Northwest
The forests of Washington are a prominent part of the state’s history, shaping its
economic development and identity since the 1850s. Washington, known as the
Evergreen State, has relied on the logging industry since its creation, but the 1994
Northwest Forest Plan dramatically altered federal land management, reducing timber
harvest by 80% on federal land to provide protection for riparian areas and late
successional reserves for species associated with old-growth ecosystems such as the
northern spotted owl (Strix occidentalis caurina) (Charnley et al. 2006). As a result,
there is increased pressure on non-federal (private, state, tribal, and county/municipal)
timberland to supply 95% of the demand (Smith 2015). In western Washington, the
average annual harvest level across all management types dropped 45% from pre-1990 to
1998-2002 (Partridge and MacGregor 2007). In Washington State there are 21 million
acres of forest, of which 8.9 million acres (42%) are working forests grown for timber
production (Lippke et al. 2007). In 2014, over 3 billion board feet of timber was
harvested in Washington (Smith 2015). Approximately 22% of Washington’s timber
supply is exported to international markets (Partridge and MacGregor 2007).
The economy of Washington, particularly rural communities, depends on these
timber plantations, dating back to the settlement of the region that was made possible by
timber harvest. Washington’s forest industry is the second largest in the nation (behind
Oregon) and drives economic activity including employment, wages, and revenue for
both state and local governments. The total direct, indirect and induced impact of
forestry-related industries included 105,000 jobs paying $4.9 billion in wages, gross
business income totaling nearly $28 billion, and $175 million in taxes paid in 2013
2

(Hatfield 2013). In 2015, more than $37 million in forest excise taxes were distributed to
counties, libraries, local schools, and taxing districts (Department of Revenue 2015).
Forest products is the third largest manufacturing sector in the state (Hatfield 2013). An
analysis of the economic impacts of SNC could not be found in Washington, but in
Oregon forests there is an impact of more than 2,100 jobs, representing $117 million in
labor income, $10 million in income tax, and $700,000 in harvest tax, for a total of $128
million per year lost due to the disease (Kanaskie et al. 2014). With a $12.7 billion forest
sector contribution to Oregon’s economy each year, this represents a loss of 4.7%
(Oregon Forest Resources Institute 2015).
Approximately 42% (11.6 billion cubic feet) of non-federal timberland in
Washington State is composed of Douglas-fir (Gray et al. 2005), underlining the
importance of this species. Waring and Franklin (1979) found that coastal stands of
Douglas-fir are among the most productive native conifer forests in the world due to a
long growing season, abundant nitrogen, high precipitation, and relatively warm winter
temperatures. Even with growth losses from SNC, Douglas-fir is still financially
competitive with other local conifer species. Western hemlock (Tsuga heterophylla) is
the primary alternative species in the area but is not as valuable as Douglas-fir, due to
market demands for quality structural lumber. Washington Department of Natural
Resources’ reported log prices in October 2015 in the Coast marketing area at $551/MBF
(thousand board feet) for Douglas-fir, compared to $449 for western hemlock (Smith
2015). Other alternative species that are worth more than Douglas-fir have their own
drawbacks: red alder is only suitable to grow in riparian areas and western redcedar,

3

while highly valuable, is browsed heavily by deer and elk as a sapling, grows slowly, and
is easily wounded during thinning operations (Shaw et al. 2011).
What is Swiss needle cast?
The life cycle of P. gaeumannii
Phaeocryptopus gaeumannii is the microfungus that causes the SNC disease.
Numerous researchers have described the life cycle of P. gaeumannii since its discovery,
which is an important first step in the field of pathology (Boyce 1940, Chastagner and
Byther 1983, Chen 1972, Ford and Morton 1971, Hood and Kershaw 1975, Hood 1982,
Michaels and Chastagner 1984a, Rhode 1937). Manter et al. (2005) identified three key
seasons in the life cycle of P. gaeumannii: May-June is when spore dispersion,
deposition, germination, and initial infection occur; August-October is when fungal
development occurs within infected needles; and December-February is the period
critical to the rate of pseudothecia (fungal fruiting body) growth.
In the spring, spores of the fungus are dispersed by windblown rain and infect
newly emerging Douglas-fir needles. The ascospores tend to be released at temperatures
between 5 and 30°C and in greatest abundance at 20°C (Michaels and Chastagner 1984a).
This is not a one-time occurrence, but occurs continuously throughout spring and summer
(Temel et al. 2004). The release coincides with bud break and shoot elongation of
Douglas-fir and only newly emerged needles can be infected (Stone et al. 2008b, Hansen
et al. 2000). Harrington and Gould (2010) predicted that budburst will occur earlier as
temperatures warm with climate change, which depending on changes in the seasonality
of precipitation, could influence SNC infection behavior. The spore germinates on the
needle surface until it finds a suitable stomata (air pore) to grow into. Infection through
4

stomata is the exclusive method of P. gaeumannii infection (Stone et al. 2008b).
Throughout the summer, the fungus colonizes the intercellular spaces of the needles
(Capitano 1999). The fungus does not penetrate cells but grows within the mesophyll
layer and on the leaf surface, absorbing water and nutrients, such as nitrogen and carbon,
from the needles’ intercellular spaces (Capitano 1999). Between October and February,
pseudothecia form in the epistomatal chamber and can be seen as tiny black spheres in
the rows of stomata (Stone and Carroll 1985) (Fig. 1). The pseudothecia gradually
mature until May to June, when the ascospores are released.

Figure 1. (A) Pseudothecia visible as black dots on the underside of Douglas-fir needles. (B)
Rows of stomata with pseudothecia. (C) Cross-section through a stoma showing pseudothecium
(p) between the guard cells (gs). From Stone et al. 2008b.

As the needles age, hyphae grow from the pseudothecia across needle surfaces in
dense mats and continue to infect more stomata (Capitano 1999). Thus, 2-year-old (and
older) needles typically have increased levels of fungal colonization (Maguire et al. 2002,
Michaels and Chastagner 1984a, Temel et al. 2004, Winton et al. 2003). Epiphytic
5

colonization in an environment with year-round leaf moisture, such as the PNW, means
that the disease can progress cumulatively over time (Capitano 1999). After several years
of favorable weather conditions, the entire tree crown can be heavily infected with P.
gaeumannii.
Effects on Douglas-fir
There is a strong physiological basis that links P. gaeumannii with disease
severity (Watt et al. 2010). The fungus interferes with key life cycle phases of Douglasfir, but does not kill the plant cells directly. The pseudothecia of the fungus occlude the
needles’ stomata, impairing gas exchange and photosynthesis, and is thus considered the
primary mechanism of pathogenicity (Manter et al. 2000, 2003a). Effects include
reduced respiration and photosynthesis, chlorosis (yellowing of foliage), decreased
needle retention, growth loss, and altered wood quality.
As pseudothecia block stomata, the entrance of carbon dioxide (CO2) into the leaf
is restricted, resulting in reduced carbon assimilation rates. Occlusion of 20% of stomata
reduces stomatal conductance by approximately 20% and daily net CO2 assimilation by
60% (Manter et al. 2003a). Another result of this decrease in CO2 is decreased activated
rubisco, which requires a molecule of CO2 for its activation and then catalyzes the first
step in carbon fixation (Manter et al. 2000). It is believed that occlusion of about 25% of
stomata results in overall negative needle carbon budgets on an annual basis (Manter et
al. 2003a). As respiration exceeds assimilation, the needles switch from being carbon
sources to carbon sinks (Cannell and Morgan 1990).

6

When stomata are occluded by pseudothecia, there is an associated decline in
photosynthesis. Manter (2002) found that SNC-infected needles had lower
photochemical utilization due to a decline in the efficiency of photosystem II, resulting in
twice as much excess absorbed light as uninfected needles. This excess light causes
photooxidative damage and might contribute to needle abscission. Unexpectedly,
severely infected trees still maintain a positive carbon budget for the year as they rely on
their current-year needles (that are infected but the fungus has not developed yet) as the
main source of photosynthate (Saffell 2013).
One of the first visible symptoms of SNC is chlorosis, or yellowing of foliage.
The mechanism causing chlorosis is not quite understood and there are certainly other
factors, such as soil conditions or pollution, which can cause chlorosis (Gowin and Goral
2015, Chappelka and Grulke 2016). Therefore, it is not used as a definitive diagnosis of
SNC but it can be used as one type of measure in conjunction with others or to identify
general areas of disease boundaries when SNC is known to exist in a particular stand.
Decreased needle retention is another symptom that can help narrow the diagnosis
to SNC. As P. gaeumannii colonization increases, photosynthetic rate of the needle
decreases, and when the cost of maintaining a needle exceeds the benefits from retaining
it, the needle is shed (Manter et al. 2000). Hansen et al. (2000) hypothesized that the
proportion of stomata occluded by pseudothecia rarely exceeds 50% so needles are shed
before half of the stomata are occluded, regardless of age.
Under ideal conditions coastal Douglas-fir can hold its needles for up to seven
years in western Oregon and Washington (Mitchell 1974), although a more typical

7

number is four years (Maguire et al. 2002). Needle longevity is related to many factors,
including latitude (Xiao 2003), climate (Coop and Stone 2007), site fertility (Balster and
Marshall 2000, Niinemets and Lukjanova 2003), and insect and disease history (Hansen
et al. 2000). Populations with high levels of SNC commonly only retain less than a year
of foliage (Maguire et al. 2002), although the average in the epidemic area is 1.5 to 2.6
years (Hansen et al. 2000). Zhao et al. (2012) studied needle longevity in the Oregon
Coast Range and found that most needles survived the first two years but were likely to
die after that.
Foliage diseases typically reduce foliage retention more in the lower crown,
probably because of moist microclimate; however, SNC is unique in that most of the
effects are seen in the upper crown (Hansen et al. 2000, Manter et al. 2003b, Shaw et al.
2014, Weiskittel et al. 2006). Warmer temperatures (that favor fungal growth) in the
upper crowns or photooxidative damage may cause the intensified symptoms (Manter
2002).
Defoliation also has implications for the ecosystem as a whole. Processes such as
nutrient cycling, decomposition rates, and soil temperature and moisture levels can all be
modified by defoliation (Kizlinski et al. 2002). Not only is the amount of litterfall
increasing, but the timing is altered as well, with foliage falling not only in the fall as per
usual, but also in the early summer, which is consistent with the lifecycle of P.
gaeumannii (Weiskittel and Maguire 2007).
Since SNC does not kill the trees it infects, the biggest concern is growth loss,
especially in plantations where the trees are grown for timber harvest. Although

8

reduction in foliage mass and thus photosynthesis is the main cause of growth loss, the
role of pseudothecia in inhibiting gas exchange on surviving foliage is also a contributing
factor (Manter et al. 2000). These different mechanisms of growth impact are reflected in
the different SNC indices used to calculate growth loss: foliage retention surveys indicate
potential growth decline due to foliage loss and pseudothecia counts represent the
potential growth decline caused by disruption of gas exchange by pseudothecia. Another
mechanism suggested by Saffell et al. (2014b) is that SNC-infected trees redirect their
carbohydrates to new needles and branches, at the expense of trunk growth.
Maguire et al. (2011) found that once infected, the decline in growth was steady,
without a threshold at which the loss suddenly appeared or worsened. They also
correlated growth loss with declines in foliage retention and calculated growth loss from
SNC as approximately 50% after a 75% reduction in foliage retention and approximately
25% after a 50% in foliage retention. Shaw (2008) made a general recommendation to
landowners to not worry about growth loss unless their trees are retaining less than three
years of foliage, at which point reduced growth is typically first detected.
Growth analyses can provide another insight in the effects of SNC. A growth
reconstruction analysis was performed by Maguire et al. (2002) in northwestern Oregon
in which they used annual height increments and stem section radial growth
measurements to calculate a volume growth loss of 23% in 1996, with the most severely
diseased plantations reaching a 52% loss. Hansen et al. (2000) estimated height growth
losses at 50 to 70%, corresponding to as much as a 30% volume growth loss. A tree-ring
analysis on older (>80 years) trees was performed by Black et al. (2010) and found that
radial growth was reduced by as much as 85% at the most severely diseased site.
9

The arrival of SNC in New Zealand provided a unique opportunity to quantify
growth increment loss. SNC was discovered there in 1959 and has been closely
monitored throughout its spread, with records of the timing of its arrival in different
forests known. Kimberley et al. (2011) analyzed these growth rates and found a
cumulative mean reduction of 32% for stem volume. The variation in the estimates of
growth loss could be due to variation in other site factors or different methodologies in
quantifying the loss; however, there is a clear consensus that growth loss on some level is
occurring.
The forest products sector relies heavily on Douglas-fir wood for structural
lumber so any changes to its quality are a concern for the industry. The ratio of
earlywood, which is formed in early spring by relying on photosynthate from older
cohorts, to latewood, dependent mostly on new foliage, dictates the structural integrity of
the wood (Onaka 1950). Johnson et al. (2003) found that latewood and earlywood
growth in SNC-infected Douglas-fir was 44 and 68% less, respectively, than trees
sprayed with fungicide (not infected with SNC). Since there was more of a growth loss
in earlywood than latewood (due to its reliance on the more heavily infected older
needles), the higher latewood proportion resulted in increased wood density. Although
this might seem like a benefit, the weakest portion of wood is earlywood and by reducing
earlywood cell wall thickness, Johnson et al. (2003) suggest that in SNC-influenced
wood, the weakest link could be further weakened.
SNC-infected trees also have a smaller sapwood area, lower sapwood moisture
content, and more gas-filled space in the sapwood, probably due to a decrease in sap flow
and specific conductivity (Edwards and Jarvis 1982, Granier et al. 2000, Puritch 1971).
10

Johnson et al. (2003) found a 21% decrease in moisture content in trees with severe SNC,
partially due to increased latewood (de Kort 1993) but also because of insufficient
photosynthate (energy) to reverse sapwood embolisms. Trees commonly refill air
embolisms in the xylem, but photosynthate is required and it is possible that diseased
trees lack the photosynthate reserves needed to reverse these common gas embolisms
(Johnson et al. 2003). The reduction in sapwood area is due to decreased foliage (Grier
and Waring 1974) and since sapwood is of higher green density and moisture content,
this would result in reduced log weights and less opportunity to use the timber for poles
or pilings (Johnson et al. 2003).
History of Swiss needle cast discovery
SNC has an interesting history, as it was first discovered outside of its native
range and the consequent knowledge of its origin and spread assisted in narrowing down
the environmental factors that control its distribution. The history of the disease offers a
parallel explanation of its geography, and in the case of a pathogen such as P.
gaeumannii that is heavily impacted by its environment, geographic location has turned
out to be a key piece of information in understanding the disease.
Worldwide spread followed by discovery in United States
The fungus that causes SNC, Phaeocryptopus gaeumannii, was first discovered in
1925 in Switzerland and within fifteen years it was identified in Douglas-fir stands across
Europe and the United Kingdom (Boyce 1940, Liese 1938, Peace 1962, Wilson and
Waldie 1928). By 1940 SNC was discovered in the northeastern United States and
reports continued to come in from Turkey, Australia, New Zealand, and Chile (Beekhuis
1978, Boyce 1940, Hood et al. 1990, Morton and Patton 1970, Osorio 2007, Marks and
11

Pederick 1976, Temel et al. 2003). Since P. gaeumannii does not live or sporulate
saprophytically (on dead organic matter), its distribution may have occurred through the
movement of infected Douglas-fir nursery stock (Stone et al. 2007a).
Later examination of herbarium specimens showed that P. gaeumannii was
present in Oregon as early as 1916 and because of its wide distribution and (up until then)
harmless effects in the Pacific Northwest, it was considered to be native to the region
(Boyce 1940). However, by the mid-1970s Christmas tree growers in the Pacific
Northwest began reporting damage from SNC, resulting in annual losses of $3.4 million
(Michaels and Chastagner 1984b). By the mid-1980s, forest managers and researchers
began noticing more frequent and severe cases of SNC in the coastal timber plantations
of Oregon and Washington.
A worsening epidemic
The 1990s saw a dramatic increase in distribution and severity of the disease. In
response, the Swiss Needle Cast Cooperative was established at Oregon State University
in 1996 and scientists began conducting aerial surveys to ascertain the geographical
extent of the disease. In 1999, approximately 119,303 ha of 1.1 million ha (295,000 ac of
2.9 million ac) aerially surveyed in coastal Oregon were classified as severely infected
(Hansen et al. 2000) and a similar survey in coastal Washington found approximately
81,000 ha of 930,000 ha (200,000 ac of 2.3 million ac) infected with SNC (Omdal and
Moore 1999).
The area of Douglas-fir showing symptoms of SNC has been increasing in
Washington, from 94,000 ha (228,500 ac) (8.5%) in 2012 to 141,000 ha (349,704 ac)

12

(14%) in 2015 (Ramsey et al. 2015) (Fig. 2). Aerial surveys have been more consistent
in Oregon and their data shows variation year-to-year but an obvious trend of rapid
increase (Fig. 3). Maguire et al. (1998) calculated a growth loss due to SNC of about 3.2
m3/ha/yr (230 board feet/acre/year) from plantations growing at a rate of 14 m3/ha/yr
(1,000 board feet/acre/year) in 1996. In Oregon this came out to be 602 m3/ha/yr (43
million board feet/acre/year) lost to the disease (Maguire et al. 1998). Observed damage
has been most severe within 18 miles of the coast, but not all coastal stands are severely
damaged (Kanaskie and McWilliams 1998, Hansen et al. 2000).

Figure 2. Washington aerial survey maps showing the spread of SNC from 2012 to 2015.
From Ramsey et al. 2015.

13

Figure 3. Area of western Oregon showing SNC symptoms during aerial surveys flown in 19962014. From Kanaskie and Norlander 2014.

Investigating the cause of the epidemic
The severity of the epidemic in Oregon has spurred a surge in research,
particularly focusing on how an inconspicuous, insignificant native pathogen could so
quickly become a serious forest health issue. A popular conceptual model in
epidemiology is the disease triangle between the causal agent (P. gaeumannii), the host
(Douglas-fir), and the environment (McNew 1960, Hansen 1996). Plant pathology
requires all three components to be present and elimination of any one can prevent
disease. Efforts to strengthen the understanding of this relationship have been ongoing
and many questions still remain. Each corner of the triangle represents a possible
explanation for the disease outbreak, some of which are examined here.
One hypothesis to explain the outbreak was that many of the coastal plantations
were established from seed collected farther inland and at higher elevations than native
14

coastal Douglas-fir stands (Maguire et al. 1998). However, professional foresters have
long known about geographic variation in tree genotypes and by 1966 many programs
were in place to assist them in appropriate selection of stock, including forest tree seed
certification by site of origin, seed zone maps, and seed transfer guidelines (Randall
1996). The interior form of Douglas-fir (P. menziesii var. glauca) is more susceptible
than the coastal form (P. menziesii var. menziesii) but foresters do not grow the interior
form in western Oregon and Washington and it does not occur naturally in the Coast
Range (Manter et al. 2005).
Kastner et al. (2001) investigated SNC susceptibility of Douglas-fir from different
seed zones. They compared growth of 50 seedlings from each of three seed sources
(coastal fog belt, western Oregon Coast Range, and standard vendor-purchased seed) in
an area heavily impacted by SNC, finding no significant difference in basal diameter,
height growth, and needle retention. Additionally, Temel et al. (2004) examined 108 15year-old Douglas-fir trees from six families, finding that the amount of P. gaeumannii on
foliage did not differ significantly. The widespread distribution of the disease in the
western Coast Range, with little variation in susceptibility among provenances and
families from that area, deems inappropriate seed source an unlikely cause of the current
epidemic.
Pathogen genetic variation is another possible explanation for the current
epidemic. The population of P. gaeumannii in North America has been found to contain
two distinct, non-recombining, sympatric lineages (Winton et al. 2001, 2006). While
Lineage 1 exists both throughout the Pacific Northwest and abroad, Lineage 2 has not
been found in any of the samples from Europe and eastern North America and has been
15

associated with more severe disease symptoms (Winton et al. 2001, 2006). Some
preliminary work by Bennett and Stone (2014) in Washington found two out of twenty
isolates that were genotyped belonged to Lineage 2, meaning that strain is present here in
small numbers. Although Lineage 2 is comprised of five genotypes, it was only
represented by a single genotype in most stands in western Oregon, which Maynard
Smith et al. (1993) classify as an epidemic population structure, with one or a few highly
successful genotypes. This is an interesting possibility that warrants further work into
differences in pathogenicity of the two lineages or individual genotypes.
Since the discovery of P. gaeumannii, local climate has been believed to be a
major cause of its pathogenicity (Boyce 1940, Hood 1982). This hypothesis has persisted
as the most widely accepted explanation for European and western North American
differences in disease severity. Much research has gone into analyzing how the annual
fluctuations in SNC severity have corresponded to annual fluctuations in various climatic
factors. A four-year study by Stone et al. (2008a) found that measures of severity within
plots with the same seed source remained at similar levels over the years, suggesting that
differences in severity between sites is due to environmental or other site factors. The
primary hypotheses regarding climate are that mild winter temperatures are more
conducive to the development of fungal mycelia in Douglas-fir needles and abundant
spring moisture encourages spore germination on needles and allows hyphae to grow
across the needle surface (Latta et al. 2009, Manter et al. 2005, Rosso and Hansen 2003,
Stone and Coop 2006).
Forest pathology requires a landscape perspective and anthropogenic impacts on
landscape patterns in relation to disease is another important perspective to examine
16

(Holdenrieder et al. 2004). A 1997 survey by the Oregon Department of Forestry found
that 80% of the 76,970 hectares of Douglas-fir plantations within 29 kilometers of the
Oregon Coast had been occupied by other species in the previous rotation (Manter et al.
2005). Much of this converted land and where SNC is most severe, lies within the Sitka
spruce (Picea sitchensis) vegetation zone (Fig. 4). Characterized as wet maritime, winter
and summer temperatures are moderate and average annual precipitation is 150 inches, in
addition to fog and clouds that contribute further moisture (Henderson et al. 1989).
Coincidentally, these are also ideal growing conditions for P. gaeumannii. The subtle
climatic differences that dictate the different vegetation zones could also be dictating
disease severity. Douglas-fir is the early seral dominant species in the western hemlock
(Tsuga heterophylla) vegetation zone, commonly bordering the Sitka spruce zone to the
east; however, Douglas-fir usually only occurs sporadically within the Sitka spruce zone,
not as pure stands (Stone et al. 2008a). This may mean that the Sitka spruce zone exists
not only because of favorable habitat for spruce and hemlock, but also because its main
competitor, Douglas-fir, isn’t able to outcompete it due to SNC in coastal environments
(Stone et al. 2008a).

17

Figure 4. Map of vegetation zone in western Washington.

The combination of increased levels of Douglas-fir within the coastal Sitka spruce
zone and a climate favorable to fungal infection and growth is the most likely cause of
the current epidemic. However, the complex gradient of moisture, temperature, and fog
within this zone is a very broad explanation and detailed climatic variables alone
(discussed in the next section) are more useful in explaining which specific conditions are
the most influential.

18

Current research
When SNC was first recognized as a problem in the Pacific Northwest, the initial
reaction was to find a cure. While there have been no outright successes to date, this is
still an area of interest to many land managers trying to develop their management
strategies. More recently the research focus has shifted to learning where are, and which
specific environmental factors are causing, the most severe disease impacts. This seems
to be the most promising avenue, to learn high-risk areas that should be avoided, but first
the disease control research will be discussed.
Attempts to control/minimize disease impacts
Traditional approaches to reduce or prevent SNC infection have met limited
success; however, landowners can practice adaptive silviculture to meet their objectives.
With techniques ranging from fungicide or fertilizer application to selective Douglas-fir
genetics, a combination that is most suitable for individual landowners’ management
goals can be formulated. The Oregon State University Swiss Needle Cast Cooperative
recommends mixed species plantations not to reduce disease severity, but to at least
minimize economic risks (Shaw et al. 2011). This can also help to provide better habitat
that is less impacted by disease for late-seral species such as northern spotted owls. In
some situations where an area is known to be high-risk, Douglas-fir simply should not be
grown and other species such as western hemlock should be considered (Kastner et al.
2001).
The fungicide chlorothalonil (Bravo) has been recommended as a disease control
measure in Christmas tree plantations for quite some time (Skilling 1981, Hadfield and
Douglas 1982, Chastagner and Byther 1983, Pscheidt and Ocamb 2005), with
19

recommendations to start applying annually three years prior to planned harvest. Crane
(2002) used elemental sulfur (Thiolux) as a fungicide, as well as chlorothalonil (Bravo)
fungicide, and found that Bravo was the most successful in reducing infection levels.
Although only one year of treatment was applied, no difference in growth (height or
diameter at breast height) was observed.
Other potential fungicides have been tested with mixed results. It has been
proposed that sulfur can act as a fungicide, decreasing disease incidence and improving
foliage color and retention (Chastagner 2002, Stone et al. 2004). However, aerially
applied treatments of sulfur and sulfur plus nutrients showed no significant increase in
volume of SNC-infected stands (Younger et al. 2008). Copper fungicide was aerially
sprayed in a Douglas-fir plantation in New Zealand with no effects; however, switching
to hand spraying the same material at the same concentration reduced the proportion of
infected needles to below 42%, compared to 100% in unsprayed controls (Hood and van
der Pas 1979). This would suggest that the hand-sprayed application covered foliage
more thoroughly.
While fungicides can be a successful method of disease control, the effects are
brief. Stone et al. (2007) sprayed chlorothalonil (Bravo) fungicide aerially for five years
and while fruiting bodies decreased and needle retention increased, these effects only
lasted one year post-treatment, probably due to decreased inoculum production, and then
foliage returned to prior levels of infection. It appears that enough residual inoculum
remained in the tree crowns to allow rapid re-infection as soon as treatments stopped
(Stone et al. 2007b). The prohibitively high costs associated with annual application as
well as the environmental risks involved with prolonged exposure of both terrestrial and
20

aquatic systems to these compounds are enough to discourage fungicides as a long-term
solution.
Soil nutrition has long been recognized as important in sustained and high
production of timber and has been found to have a significant impact on biomass
production and overall growth (Mitchell et al. 1996). In particular, nitrogen fertilization
as urea has been common in the Douglas-fir region of the Pacific Northwest (Bengston
1979). However, Filip et al. (2000) suggest that nitrogen fertilization may be worsening
SNC severity. Waring et al. (2000) found a strong correlation between increased foliar
nitrogen concentration, low soil calcium and low soil pH, and decreased foliage retention,
possibly due to excess nitrogen being stored as soluble amino acids that promote the
growth and development of P. gaeumannii. El-Hajj et al. (2004) used nitrogen (urea) to
fertilize Douglas-fir and found 2.2 to 3.6 higher levels of pseudothecia density on 2-yearold needles. Some managers have begun to fertilize with lime to lower the ratio of
nitrogen to other essential nutrients (Mulvey et al. 2013).
It is true that fertilizer treatments can impact disease severity in different ways,
depending on the pathosystem, the specific application materials, timing of application,
and other factors (Datnoff et al. 2007, Engelhard 1989). Fertilization may reduce disease
by bolstering plant resistance or tolerance but may also increase disease by improving
pathogen access to nutriment through its host (Mulvey et al. 2013).
Many researchers have found that fertilization has neither positive nor negative
effects on P. gaeumannii severity. An experiment on fertilization impacts of nitrogen
(urea), calcium as lime (calcium carbonate), calcium as calcium chloride, phosphorus

21

(monosodium phosphate), and a site-specific blend resulted in no significant effect on the
P. gaeumannii infection levels of Douglas-fir both across and within sites (Mulvey et al.
2013). Crane (2002) found that fertilizer (N-P-K) treatments had no significant impact
on growth of trees affected by SNC. Mainwaring et al. (2009) also looked at foliage
retention, volume growth, form quotient, and sapwood area in response to seven types of
fertilizer treatments, finding no improvements. Realistically, managers should assess the
soil chemistry at each site and fertilize accordingly, but not expect it to have much effect
on SNC.
Although traditional fertilization does not appear to affect SNC, soil nutrition still
may contribute to Douglas-fir susceptibility in other ways. The soil microbial
community is a key component of stable and healthy growing conditions and some
common types of ectomycorrhizal fungi commonly found with Douglas-fir, such as
Cenococcum and Rhizopogon, were found to be less widespread in SNC stands than
uninfected stands (Luoma and Eberhart 2014). This suggests that “stress tolerant”
ectomycorrhizal fungi may be important for sustaining Douglas-fir against the disease.
Pre-commercial thinning is a common management practice in young timber
stands where high stand densities limit individual tree growth and leave trees more
susceptible to insects and disease (Mitchell et al. 1983). Intraspecific and interspecific
competition can also decrease resource availability and reduce tree growth (Cole and
Newton 1987). Some suspect that thinning can increase air circulation, resulting in a
drier microclimate, in which the fungus will not grow as well. Conversely, it is possible
that the stress of thinning in stands already damaged by SNC may actually have negative
impacts on residual trees (Filip et al. 2000).
22

Mainwaring et al. (2005) found that pre-commercial thinning does not intensify
disease development. Infected stands do respond positively to thinning but growth is still
lower than in uninfected stands. Severely infected stands experienced a volume growth
loss of 36% when thinned (Mainwaring et al. 2005), compared to Maguire et al. (2002)’s
finding of 50% in unthinned stands. In northwest Oregon, monitoring four seasons after
thinning resulted in no difference in needle retention, positive or negative (Kanaskie et al.
2002). Thinned stands in New Zealand had infection rates similar to unthinned controls
and had as much foliage five years after thinning (Hood and Sandberg 1979).
The overall recommendation is that thinning in low- or moderate-severity stands
will still be beneficial in most stands, but should be avoided in high-severity stands (Filip
et al. 2000). Even if thinning does not produce results acceptable for timber production,
it can be a reasonable strategy in forests managed for timber along with other purposes
such as wildlife and aesthetics (Oliver 1992, Oregon Department of Forestry 2001).
Douglas-fir trees growing within the same environment can exhibit different
levels of symptoms, due in part to each tree’s genetics (Johnson 2002, Temel et al. 2005).
The main focus of genetic testing has revolved around determining if trees exhibiting less
severe SNC symptoms are more resistant (less fungal colonization) or more tolerant
(retained foliage under similar levels of infection) (Temel et al. 2004). Temel et al.
(2004) examined trees from six families, categorizing them into three disease severity
groups: mild, moderate, and severe. From this study, they found that the amount of P.
gaeumannii did not differ significantly between the groups that were exhibiting different
levels of symptoms; therefore differences in severity were attributed to tolerance, rather
than resistance. Hood and Kimberley (2005) found similar results in New Zealand.
23

This variation in tolerance appears to be a result of variation in environmental
conditions. Many researchers have noted that susceptibility and symptom severity are
higher in Douglas-fir genotypes originating from areas of lower rainfall and humidity
(Hood 1982, McDermott and Robinson 1989, Stephan 1997). The reasoning is that
higher rainfall and humidity increase disease pressure, resulting in increased selection
pressure for disease resistance to SNC. Therefore, seed source originating from the
interior Rocky Mountain form of Douglas-fir (var. glauca) is more susceptible to the
disease than the coastal form (var. menziesii) when grown together in provenance trials
(Hood 1982).
The practical outcome of this research is that family selection for SNC tolerance
at the seedling stage could be used to increase tolerance of managed stands. Foliage traits
of crown density and color are reasonable indicators of tolerance, which are fairly simple
to assess (Johnson 2002). This would also give land mangers a head start on culling
poorly performing trees during thinning as the trees age.
Increasing our understanding of the disease: the importance of monitoring surveys
The first step in studying plant pathogens is to obtain an accurate measure of
pathogen abundance. There is an important distinction between disease symptoms and
signs: a symptom is a visible change in the plant, whereas a sign is the actual presence of
the organism causing the disease (Temel et al. 2004). Some new methods of quantifying
fungal colonization have been established, such as ergosterol content analysis, where a
cell membrane sterol found only in fungi is measured for fungal biomass (Manter et al.
2001, Winton et al. 2003) and quantitative PCR, where amplification of fungal DNA with
a polymerase chain reaction is monitored in real-time (Winton et al. 2003); however, the
24

more widely used methods of needle retention surveys, aerial surveys, and pseudothecia
counts will be discussed here.
Since foliage loss is a primary symptom of SNC, needle retention surveys are a
straightforward, easy to assess method that is widely used. Needle retention is typically
estimated on a scale of 0 to 9, with 0 representing 0-9% retention and 9 representing 90100% retention. Ideally three to five years-worth of needles are evaluated on each tree
and then averaged together. Needle retention is best surveyed in April and May by
examining lateral branches in the middle to upper crown of at least ten randomly chosen
dominant or codominant trees (Fig. 5).

Figure 5. A healthy Douglas-fir (left) compared to one showing decreased needle retention due
to SNC (right). From the Oregon Department of Forestry.

25

When the symptoms of foliage color, foliage density, needle color, and needle
retention were compared to levels of infection (signs), needle retention was the only
related trait (Temel et al. 2004). Needle retention also shows a strong positive correlation
with tree growth, which is a primary concern of many surveyors (Maguire et al. 2002,
2011). The ease of foliar retention surveys translates to wider geographic areas that are
able to be surveyed and a more accessible method for landowners. However, the
objectivity of this method is questionable. Temel et al. (2005) pointed out that these
visual assessments could be quite subjective in assigning numbers on a continuous scale
of 0-9, leading to questions of their value.
In 1996 the Oregon Department of Forestry began flying annual aerial surveys to
assess the extent of damage caused by SNC, through the sponsorship of the Swiss Needle
Cast Cooperative. Objectives are “to identify and map areas of Douglas-fir forest with
obvious symptoms of SNC in the Oregon Coast Range; and to monitor change over time
in the amount of forest with visible symptoms of the disease” (Maguire et al. 1998, p.
705). Flights are typically flown in April or May and areas showing the color signature
of SNC chlorosis are drawn as polygons on topographic maps. It is important to note that
aerial surveys only map where symptoms are severe enough to be visible from the air and
are not meant to be a comprehensive inventory. Another complication is the fact that
chlorosis can be caused by other factors besides SNC, and appear in stands that aren’t
even composed of Douglas-fir so overestimation is a possibility as well. The idea is to
map general areas to obtain acreage estimates for documenting trends over time
(Kanaskie et al. 2001).

26

Aerial surveys are costly and have many limiting factors including varying
weather conditions, which can affect the appearance of chlorosis and smaller areas that
may be overlooked (Hilker 2014). Kanaskie et al. (2002) acknowledged that the same
areas sometimes were not mapped each year due to timing of the survey, cloud conditions
at the time of flight, changes from harvesting, and precision errors in sketch-mapping
polygons. However, the value in being able to get a picture of the landscape as a whole is
undeniably important in monitoring a widespread disease such as SNC.
Pseudothecia counts are commonly recommended as the preferred method for
quantifying SNC due to their high correlation with symptom severity (Hood 1982,
Michaels and Chastagner 1982a, Hansen et al. 2000, Manter et al. 2001, Winton et al.
2003). Typically ten one-year-old and ten two-year-old needles per tree are examined
under a microscope to count the percentage of stomata occluded. “Because the
physiological effects of the disease (impaired CO2 uptake and photosynthesis) are
quantitatively related to the abundance of the pathogen (proportion of stomata occluded
by ascocarps), pathogen ascocarps abundance [pseudothecia counts] is a suitable
response variable for assessing effects of climatic factors on disease” (Stone et al. 2008a).
While needle retention surveys and aerial surveys are operationally useful, the best way
to understand the epidemiology of this outbreak is by observing the response of the
pathogen itself, i.e. pseudothecia counts. Winton et al. (2003) found a -0.644 Pearson
correlation coefficient between the pseudothecia count and needle retention, whereas
ergosterol content was only -0.578 and quantitative PCR was only -0.451. There is also a
proven pathway that exists between pseudothecia density and physiological impacts
(Manter et al. 2000).
27

Some challenges associated with pseudothecia counts are high labor and statistical
challenges. Costs of equipment are low with microscopes being the only major cost, but
manually counting stomata and pseudothecia is time-consuming and subject to
misidentification error (Winton et al. 2003). Since only a small fraction of stomata are
examined and pseudothecia can be very unevenly distributed, clustering can result in
estimates that are too high or too low (Winton et al. 2003).
Identifying favorable conditions
Various environmental conditions such as climate, topography, soil
characteristics, and forest stand characteristics are associated with disease in Oregon
(Rosso and Hansen 2003). By studying the natural spatial and temporal variations of the
disease, we can increase our understanding of the outbreak and isolate the conditions that
facilitate fungal growth. In 1940, Boyce hypothesized that the most likely explanation
for differences in how the disease was expressing itself in Europe versus the United
States was climatic differences, specifically the humid, rainy summers in Europe that the
disease thrived in, compared to the warm, dry summers of western North America.
Spatial variation (both topographical and within each tree) in how the disease is
expressed is high across forest plantations (Hansen et al. 2000). Disease severity tends to
fluctuate from year to year; however, the relative ranking of sites by severity has
remained mostly constant, which leads researchers to believe that site-related factors play
an important role in disease severity (Hansen et al. 2000, Stone et al. 2001).
Much research has gone into climatic factors, but additionally, studying different
temporal scales is recommended. Zhao et al. (2012), Stone et al. (2007), and Manter et

28

al. (2005) looked at climatic variables at the annual, seasonal, and monthly scales, finding
that the seasonal variables were most suitable according to statistical scores, which makes
sense considering the life cycle of P. gaeumannii. In contrast, Zhao et al. (2011)
performed a similar study and found that annual and monthly variables explained more
variation than seasonal variables. In New Zealand, Watt et al. (2010) found monthly
variables to have the strongest correlations. The scale being used is critical, as Zhao et al.
(2011) predicted an increase in foliage retention with their annual and monthly models,
but a decrease in foliage retention with their seasonal model. While the annual resolution
seemed adequate to Zhao et al. (2011), they cautioned that the possibility of greater
monthly variation in future climate could deem the monthly resolution most accurate.
Free (surface) moisture on needles provides ideal conditions for spore
germination and initial infection (Stone et al. 2008b). Capitano (1999) identified free
moisture as a key factor in hyphal growth of P. gaeumannii in culture after observing that
dry conditions for 24 hours or more significantly reduced germination and growth.
Infection of inoculated needles occurred after 24 hours of exposure to moisture (Capitano
1999). However, high amounts of spring rainfall and summer fog in coastal Oregon (and
Washington) may negate the importance of this as a limiting factor (Manter et al. 2003b).
Most of the severe disease symptoms appear in the low elevation coastal fog zone,
so the amount of free water on foliage during summer months is another possible
contributing factor to disease severity (Hansen et al. 2000, Rosso and Hansen 2003).
Saffell et al. (2014a) used stable isotopes of carbon and oxygen in Douglas-fir tree rings
and western hemlock as a non-susceptible reference species to identify changes in growth
that could be related to climate factors. Results found that high relative humidity in the
29

previous two summers was most strongly correlated with the diagnostic tool of decreased
tree-ring Δ13C, and thus disease severity. The researchers speculated that this was due to
higher leaf wetness from increased nightly dew frequency, lower evaporation rates of
dew, and less spores washed off than rainfall, all resulting in more successful germination
on foliage.
Zhao et al. (2012) identified March precipitation as a general surrogate for spring
wetness, due to its correlation with late spring precipitation. Rosso and Hansen (2003)
categorized variables of fog occurrence, precipitation, vapor pressure deficit, altitude, and
aspect all into the category of “moisture” that was correlated with higher SNC severity.
Precipitation has long been believed to play a critical role in the spread of SNC.
Rainfall during the infection period aids the spread of ascospores and contributes to the
moisture discussed above (Stone et al. 2008b). Hood (1982) observed a positive
correlation between spring rainfall and P. gaeumannii abundance with more than 80% of
needles infected in wet areas, compared to only 5% in the rain shadow of eastern
Vancouver Island, Olympic Peninsula, and Coast Mountains of British Columbia.
Precipitation during the infection period of May and June has been recognized as a
contributor to regional variation in British Columbia (Hood 1982, McDermott and
Robinson 1989). In New Zealand, Watt et al. (2010) found a significant quadratic
correlation with November (late spring) rainfall. Fungal colonization increased until 149
mm per month was reached and then declined, possibly due to ascospores being diluted
or washed off needles.

30

In the United States, Zhao et al. (2011) found that foliage retention decreased with
greater precipitation with the greatest influence coming from spring and early summer
precipitation. Spring and summer precipitation was a key model input for Manter et al.
(2003c, 2005) during their greenhouse studies. Lee et al. (2013) examined Douglas-fir
tree-ring chronology records dating back to the 1590s, with nonsusceptible western
hemlock as the climate proxy, and found that summer precipitation was correlated with
SNC impact. Regional climate trends are reflected in SNC severity as well, seen by the
1.6 to 2.6 cm per decade increase in precipitation in coastal Oregon and Washington
since 1966 (U.S. Department of Commerce, National Oceanic and Atmospheric
Administration 2005).
Warm conditions, identified by variables such as winter temperature, vapor
pressure deficit, altitude, and aspect, were positively correlated with SNC severity (Rosso
and Hansen 2003). Other studies have shown that P. gaeumannii ascospore production
(Michaels and Chastagner 1984a) and hyphal growth and germination (Capitano 1999)
increase with temperature. Labwork by Capitano (1999) found that optimum germination
and growth temperatures were 18°C and 22°C, respectively.
Manter et al. (2003c, 2005) found that average winter (December-February) daily
temperature had the biggest influence on the disease, likely acting as the limiting factor in
fungal colonization and growth. Similar results were also found in New Zealand, with
mean June (winter) temperature accounting for 53% of the variance in fungal
colonization (Stone et al. 2007a). The extreme growth losses documented in forests older
than 80 years by Black et al. (2010) were associated with warm conditions in late winter
and early spring. Winter temperatures were also found to be a strong correlative in the
31

tree-ring analysis dating back to the sixteenth century by Lee et al. (2013). Disease
severity models in western Oregon based on winter temperature were found to explain
77% and 78% of the variation in one- and two-year-old needles, respectively, and 80% in
New Zealand (Stone et al. 2007a).
Climate-based models created by Zhao et al. (2011, 2012) found that increasing
summer temperature, decreasing winter temperature, or increasing difference between the
two resulted in increased foliar retention. The influence of summer temperature is not
supported by other studies, and Zhao et al. (2011) suspect the reason it came up in their
analysis was due to other mechanisms occurring during summer, such as the negative
effects of high vapor pressure deficits, low water potential within foliage, low water
availability to fungal hyphae, and water stress on the tree itself (Zhao et al. 2011).
Manter et al. (2003c, 2005) also found that summer temperature (July maximum)
corresponded to lower disease values probably because high summer temperatures
combined with low moisture may inhibit fungal development.
Regional climate trends also seem to correspond with the increased SNC severity
seen since the 1990’s (Manter et al. 2005). Temperatures in the Pacific Northwest have
increased by approximately 0.8°C over the last century, with most of that change
occurring over winter months (Mote et al. 1999). In coastal Oregon and Washington,
average January to March temperatures have increased by approximately 0.2 to 0.4°C per
decade since 1966 (U.S. Department of Commerce 2005).
Manter et al. (2005) used their climate-based model to calculate that a 1°C
increase in average daily winter temperature corresponds to an increase of 3.3 and 5.9%

32

in P. gaeumannii colonization for one- and two-year-old needles, respectively.
Predictions for continued regional warming of 1.5°C by 2020 and 2.3°C by 2040 (Mote
et al. 1999) therefore suggest that SNC severity is likely to increase (Manter et al. 2005).
However, there is uncertainty in these climate predictions and one possible outcome is
that spring moisture will become more limiting to fungal colonization than it currently is,
resulting in winter temperatures being less relevant to disease severity (Zhao et al. 2011).
Lee et al. (2013) hypothesize that continued warming in the coastal fog zone will increase
SNC intensity and frequency, since needle wetness is not a limiting factor, but in areas
where summers are dry, continued warming and drying will likely decrease SNC
intensity and frequency.
Lack of environmental condition analysis in Washington
The relative importance of different climatic factors varies spatially. For
example, Stone et al. (2008a) found that winter temperature was the best predictor of P.
gaeumannii abundance in coastal sites (where wetness isn’t a limiting factor) but spring
leaf wetness was a more accurate predictor for inland sites. Similarly, Lee et al. (2013)
found that winter conditions were more strongly associated with disease impact at wetter,
cooler sites, but summer conditions were more important at less humid, warmer sites.
Stands experiencing similar climatic conditions but lighter spore loads may be protected
by lower disease pressure, resulting in the same climate variables having less of an effect
on needle longevity (Zhao et al. 2012).
While Oregon and Washington have fairly similar climatic conditions, there are
subtle differences that may impact the prevalence of SNC. Manter et al. (2003, p. 349)
state that “relatively slight differences in microclimate can influence the colonization of
33

foliage by P. gaeumannii as well as the severity of disease symptoms.” Hansen et al.
(2000) noted that plantations of the same age and seed source frequently exhibited fewer
disease symptoms if located just a few miles further inland or a few hundred meters
higher in elevation. These nearby sites had subtle environmental differences but those
differences may be significant. Care must be taken when using models outside the area
for which they were created, as Zhao et al. (2012) found that another model (Latta et al.
2009) had significantly underpredicted foliage retention at nearly every site that occurred
outside the geographic range.
An analysis on climatic factors associated with SNC severity in Washington
specifically has not been completed. Considering the site-specificity of the disease’s
behavior, it could be that different variables are more strongly correlated with severity. It
could also turn out to be the same as in Oregon; however, an analysis must be done in
order to identify those variables.
Once this information is known, high-risk areas for SNC can be identified.
“…Geographic variations in environmental determinants of pathogen growth rate could
lead to predictable spatial patterns of disease severity in a long-lived, perennial host”
(Manter et al. 2005, p. 1263). Identifying high-risk areas can help forest managers adjust
their harvest schedules and species planting plans. Plantations in western Oregon have
undergone unexpected changes in species composition whereby natural regeneration of
western hemlock is replacing Douglas-fir (Hansen et al. 2000). Many landowners are
also purposely planting more mixed species or switching entirely to species other than
Douglas-fir. Perhaps Douglas-fir is no longer a suitable plantation species in the coastal
Pacific Northwest due to SNC.
34

The importance of using an adaptive management framework to understand and
respond to this epidemic is increasingly important in light of climate change. The Pacific
Northwest is expected to have warmer and wetter winters (Mote and Salathe 2010),
which could result in increased intensity, frequency, and range of SNC over the twentyfirst century (Zhao et al. 2011, Watt et al. 2011). The pathogen appears to be responsive
to slight variations in climate, and warmer, moister winters will likely increase infection
rates. Thus, plantations that were only considered low-risk when planted might
experience increased levels of impact in the changing climate (Watt et al. 2010).
However, this also might provide some opportunity to extend the species range into areas
that were previously unsuitable for Douglas-fir (Watt et al. 2010). Model simulations of
natural vegetation in western Washington over three different future climate scenarios all
showed the disappearance of optimal conditions for the Sitka spruce zone by 2100, with
the western hemlock zone remaining the most extensive and the Douglas-fir zone
growing (Conklin et al. 2015). Due to the specific windows in the life cycle of P.
gaeumannii, the timing of changes in temperature and precipitation will dictate how SNC
responds.
Conclusion
The current SNC epidemic appears to be a result of many factors. The rise in
Douglas-fir plantations due to their economic value has increased the abundance of the
fungal host species, and therefore inoculum, in the area most favorable for the growth and
reproduction of the pathogen. Unfortunately, the environment that Douglas-fir grows
well in is also the environment in which P. gaeumannii grows well. The current
epidemic is likely the result of several weak points in the disease triangle.
35

Since the disease is not showing any signs of diminishing in the Pacific
Northwest, we must learn to manage our forests in coexistence with it. To make these
informed decisions, we need (1) an accurate description of the incidence and severity of
the disease, and (2) some insight into climatic variables that encourage fungal growth.
With this knowledge, Washington landowners can choose the most suitable locations for
planting Douglas-fir and adjust their silvicultural strategies to meet their own goals.

36

CHAPTER II. Manuscript
Introduction
Swiss needle cast (SNC) is a foliage disease that exclusively affects Douglas-fir
(Pseudotsuga menziesii). The pathogen was first described in Douglas-fir transplanted
from its native range in the Pacific Northwest region of North America to Europe. In the
1970s, widespread symptoms were recognized in coastal Oregon and Washington, first in
Christmas tree plantations, then in timber plantations. There are many mysteries about
SNC extent and behavior in response to changing commercial plantation practices,
climate change, and potential changes of pathogen or host. This thesis uses field data to
examine the current extent and behavior of the disease along the coast of Washington
State.
SNC is caused by the fungus, Phaeocryptopus gaeumannii. Symptoms include
chlorotic (yellow) needles, decreased foliage (needle) retention, and reductions in growth;
however, tree mortality is rare. Although SNC occurs throughout the natural range of
Douglas-fir, the most pronounced expression is along the outer coast of Washington in
the Sitka spruce forest zone.
In the early 1990s, SNC reached epidemic levels in Douglas-fir plantations of the
Pacific Northwest. It is believed that prior outbreaks had occurred, but the level of
severity and length of outbreak is unprecedented. Climatic factors are believed to have
some effect, but many subtle factors can be involved and there is geographic variation in
severity. The environmental factors that appear to influence the extent and severity of the

37

disease include topographical features, such as elevation and aspect, and climatic factors,
such as temperature and precipitation.
Tree-level quantification of SNC severity is time-consuming and labor intensive,
but pseudothecia (fruiting body) counts are unique in directly quantifying the amount of
fungus, as opposed to broad estimates of severity based on symptoms. On a landscape
level aerial surveys have been used to estimate disease occurrence by observer
interpretation of foliage color, but there have been few efforts to link the two scales of
survey. Aerial surveys have taken place in Oregon every year since 1996, but have
occurred more sporadically in Washington. Both states have shown a dramatic three-fold
increase in the acreage affected by SNC according to these aerial surveys.
Viewing the epidemic as a pathologist
Biotic (fungi, insects) and abiotic (temperature, moisture) factors are involved in
what is commonly visualized as a “disease triangle.” This conceptual model helps
visualize that a susceptible host, virulent pathogen, and favorable environment are all
required in order for disease to develop (Fig. 6). While humans are not directly
represented on one of the vertices, they undoubtedly play a role in this interaction.

38

Figure 6. The disease triangle showing the interaction between pathogen, environment, and host
that results in plant disease. From Agrios 2005.

SNC is caused by the pathogenic fungus, Phaeocryptopus gaeumannii, and is
believed to have always existed in northwestern North America. P. gaeumannii has
likely been transported to other areas around the world with the introduction of Douglasfir from northwestern North America, but otherwise has not been affected by humans.
However, humans have altered the other two vertices of the disease triangle allowing the
fungus to proliferate. Douglas-fir, P. gaeumannii’s only host, is now grown is large
monocultures outside of its range of historic dominance, not only increasing the host
abundance, but also placing it in the coastal environment that the fungus thrives in. Also,
current climate trends are warmer and wetter making conditions more favorable for
fungal growth. As a result of these factors, fungal abundance has also grown, causing the
current SNC epidemic in the Pacific Northwest.
39

During the time the northwestern United States was being colonized, old-growth
forests were increasingly cleared for settlement and timber production. Larger scale
clearcuts became increasingly common as logging technology and new machinery
progressed. Around the 1950s, a new type of forestry developed in which stands were
logged in shorter rotations and replanted with monocultures (single species) known to
grow quality wood more quickly. The extent of Douglas-fir in the forests of the outer
coast grew from scattered, rare individuals to the dominant species on the landscape.
This human intervention provided unprecedented access to the “host” aspect of the
disease triangle.
More recently, climate change has emerged as an all-encompassing effect on the
environment. No longer a debate, scientists agree that Earth’s climate is warming due to
anthropogenic effects. While different parts of the world are experiencing these changes
in different ways, there is now a new “normal,” or rather a lack thereof. The Pacific
Northwest has already experienced a regionally averaged warming of about 1.3° F, with a
projected increase in average annual temperature of 3.3° F to 9.7° F by 2070 to 2099
(Mote and Snover 2014). While precipitation trends have both increased and decreased
depending on location, season, and time period of analysis, most models agree that the
Pacific Northwest will see increased precipitation during spring, winter (up to 20%), and
fall with decreased precipitation during summer (Walsh et al. 2014). These seasonal
changes of warmer and wetter coincide with the life cycle of P. gaeumannii, whose spore
deposition and initial infection occurs in spring and pseudothecial proliferation occurs in
winter. Anthropogenic climate change clearly represents a human impact on the
“environment” aspect of the disease triangle.
40

Searching for climate correlations
It is understood that environment plays a role in virtually all forest diseases, but it
can be more difficult to pin down specific variables that have the strongest effects. While
warm and wet are very general environmental conditions, they can be further delineated
into variables such as continentality (the difference between warmest and coldest days),
heat-moisture index, and frost-free period. By identifying which variable or combination
of variables are most strongly correlated with severe levels of SNC, a more specific set of
environmental conditions that foster disease growth can be identified.
This type of analysis has been completed in Oregon and New Zealand, but not in
Washington. Due to subtle changes in environment having potentially large impacts on
fungal growth, it is important to analyze different geographic areas separately. Although
Oregon and Washington are geographically close and have similar climates, they are not
identical. This research will first answer the question: What is the incidence and severity
of Swiss needle cast in Washington? The first step in understanding any disease is getting
an accurate measure of where it is occurring, the level of infection, and preferably, how it
is changing over time. The Washington Department of Natural Resources (WA DNR)
completed these surveys in 2011 and 2012, and the 2015 survey was included in this
graduate research. The second research question is: What climate variables are most
correlated with disease severity? Models developed in Oregon and New Zealand were
tested with the data from Washington to see if similar variables could be identified as
being related to disease. From this, models could be created to guide land managers to
areas that are suitable for Douglas-fir plantations. While they are a preferred species,
some areas may be too high-risk to grow healthy (and profitable) stands of Douglas-fir.
41

Methods
The objective of this thesis was to further examine SNC in western Washington
through two means. First, the incidence and severity of the disease was quantified by
collecting needle samples from 47 sites throughout western Washington during April and
May of 2015. Data from surveys completed in 2011 and 2012 was also included in the
analysis to further our understanding of how the disease is (or is not) spreading or
intensifying over time. Second, an analysis to find correlation between disease severity
and climate variables was performed in order to understand the specific conditions under
which P. gaeumannii is most active in Washington. A range of environmental variables
such as average winter temperature and spring precipitation were calculated for each
sample site through the software, ClimateWNA, and linear regressions were run in JMP
with the colonization indices of each site.
Field assessments
The study area consisted of 47 sites throughout western Washington (Fig. 7,
Appendix A). This area covered the entire length of the state north to south (46.19° N to
48.21° N latitude) and ranged from the coast to Capitol Forest (123.22° W to 124.63° W
longitude). According to the Western Regional Climate Center (2016), this “rainforest”
area west of the Olympic Mountains receives the heaviest precipitation in the continental
United States. Annual precipitation is 178 to 254 cm (70 to 100 inches) in the Coastal
Plains and more than 381 cm (150 inches) along the western slopes of the Olympic
Mountains. Average maximum temperature in July is 21° C (70° F) along the coast and
24° C (75° F) in the foothills. Minimum temperatures in January range from 0° to 3° C
(32° to 38° F), with warmer areas near the coast (WRCC 2016).
42

Figure 7. Map of 2015 ground survey sites in western Washington.

Sites were chosen based on previous years’ survey locations. When possible, the
same site was visited; however, some sites were inaccessible due to locked gates,
construction, or logging activity. Additionally, the trees at some sites had grown too tall
to enable sampling with pole pruners. In these instances, a nearby similar, but shorter
stand was selected as a replacement. Most stands are part of large timber company
holdings where the trees are harvested in varying rotations, enabling this ease of
43

substitution. Sites were located in Douglas-fir plantations of the same age, approximately
10 to 15 years old, primarily due to previously mentioned logistics, but also to minimize
variation in canopy condition.
Transects were run at each location to collect stand data. Each transect was 75 m
beginning approximately 15 m into the stand from the road and consisted of five points
spaced 15 m apart. At each point, one dominant or codominant Douglas-fir was selected
to be sampled from alternate sides of the transect, equaling a total of ten trees sampled at
each site (Fig. 8). Field data was recorded with an electronic tablet. For consistency with
previous surveys, initial samples were collected with the help of one of the DNR forest
pathologists who completed the 2011 and 2012 surveys.

Figure 8. Layout of the 75 m transect used at each site for sampling.

Site conditions were also documented along each transect. These conditions
included landscape position, elevation, aspect, stand color, average tree age, stand
density, and species composition. Landscape position (coast, valley, ridge top, etc.),
elevation, aspect, and coordinates were recorded. The stand as a whole was assigned a
44

number for the crown color, or degree of discoloration, ranging from 1 (normal green) to
4 (severe yellow or yellow-brown). Average tree age was determined based on the
number of whorls on the Douglas-firs. At the second and fourth sampling points along
each transect, 40 m2 fixed radius plots were used to calculate stand density by counting
the number of trees in the plot and tree species composition by counting the number of
each tree species of tree.
Individual trees were also evaluated for needle retention and crown color. In most
cases, unless not clearly visible or in some way abnormal, the fifth whorl from the top of
the tree was examined. The secondary laterals (coming off the side of the main branch)
were examined for each of the past four years of growth to estimate the percentage of
needles remaining on the branch. A 0 to 9 scale was used, in which 0 represented 0 to 10
percent of needles present and 9 represented 90 to 100 percent of needles present. The
fifth whorl was also evaluated for crown color using the same scale used at the stand
level. One-year-old and two-year-old foliar samples were collected from the fifth whorl
with pole pruners and stored in paper bags (Fig. 9). Tree diameter at breast height (DBH;
1.3 m) was also measured.

45

1
2
3
4
5
6
7

Figure 9. Location of branch sampled: fifth whorl from the top of the tree (left) and first and
second cohort from a secondary lateral branch (right). Figure adapted from Temel et al. 2004.

Quantifying SNC severity
Branch samples were stored in paper bags in a refrigerator until processed, for a
maximum of 3 to 4 days. Tweezers were used to carefully remove 15 to 20 needles from
each branch and then 10 were selected that were relatively untwisted, whole, and of
similar length. Those needles were arranged onto an index card with double-sided tape,
ready for microscopic examination.
With the microscope adjusted to view approximately 50 stomata in each column,
incidence and severity was recorded (Fig. 10). Incidence, the presence or absence of
pseudothecia (fungal fruiting body), was recorded as 1 (present) or 0 (absent) by scanning
the entire needle. Next, the basal, middle, and upper thirds of each needle were examined
to count the number of pseudothecia present to measure severity. Within each third, 50

46

stomates were counted in one row on each side of the midrib for a total of 300 stomates
counted per needle.

Figure 10. Microscopic view of pseudothecia on the underside of a Douglas-fir needle. Photo by
Sue Hagle Service Archive.

Climate Data
Climate data was calculated through the software ClimateWNA v5.21 (Wang et
al. 2012), from the University of British Columbia’s Centre for Forest Conservation
Genetics. The program extracts and downscales PRISM (Daly et al. 2008) generated
monthly data (2.5 x 2.5 arcmin) and calculates annual, seasonal, and monthly climate
variables for specific locations by latitude and longitude input. The output is 23 annual,
56 seasonal, and 168 monthly climate variables (Table 1). In the output for these 47
sites, most of the solar radiation (RAD) values were incorrectly reported as 0, so that
47

variable, along with any others that included RAD as part of their calculation (Hargreaves
reference evaporation and Hargreaves climatic moisture deficit) were eliminated for this
analysis. Additionally, while Climate WNA reported data for winter, spring, summer,
and fall of the year entered (i.e. 2013 for the two-year-old needles collected in 2015), the
life cycle of P. gaeumannii involves spring infection so the winter (2013) data initially
reported was substituted with the following winter (2014) to align with the fungal life
cycle.

48

Table 1. ClimateWNA variables tested for correlation with disease severity.
1) Annual variables:
MAT
MWMT
MCMT
TD
MAP
MSP
AHM
SHM
DD<0
DD>5
DD<18
DD>18
NFFD
FFP
bFFP
eFFP
PAS
RH

mean annual temperature (°C)
mean warmest month temperature (°C)
mean coldest month temperature (°C)
temperature difference between MWMT and MCMT, or continentality (°C)
mean annual precipitation (mm)
mean annual summer (May to Sept.) precipitation (mm)
annual heat-moisture index ((MAT+10)/(MAP/1000))
summer heat-moisture index ((MWMT)/(MSP/1000))
degree-days below 0°C, chilling degree-days
degree-days above 5°C, growing degree-days
degree-days below 18°C, heating degree-days
degree-days above 18°C, cooling degree-days
the number of frost-free days
frost-free period
the day of the year on which FFP begins
the day of the year on which FFP ends
precipitation as snow (mm) between August in previous year and July in
current
year relative humidity (%)
mean annual

2) Seasonal variables:
Seasons:
Winter (_wt)
Spring (_sp)
Summer (_sm)
Autumn (_at)

Dec. (prev. yr) - Feb for annual, Jan, Feb, Dec for normals
March, April and May
June, July and August
September, October and November

Tave_wt, sp, sm, at
Tmax_wt, sp, sm, at
Tmin_wt, sp, sm, at
PPT_wt , sp, sm, at
DD_0_wt, sp, sm, at
DD5_wt, sp, sm, at
DD_18_wt. sp, sm, at
DD18_wt, sp, sm, at
NFFD_wt, sp, sm, at
PAS_wt, sp, sm, at
RH_wt, sp, sm, at

winter, spring, summer, autumn mean temperature (°C)
winter, spring, summer, autumn mean maximum temperature (°C)
winter, spring, summer, autumn mean minimum temperature (°C)
winter, spring, summer, autumn precipitation (mm)
winter, spring, summer, autumn degree-days below 0°C
winter, spring, summer, autumn degree-days below 5°C
winter, spring, summer, autumn degree-days below 18°C
winter, spring, summer, autumn degree-days above 18°C
winter, spring, summer, autumn number of frost-free days
winter, spring, summer, autumn precipitation as snow (mm)
winter, spring, summer, autumn relative humidity (%)

3) Monthly variables
Tave01 – Tave12
TMX01 – TMX12
TMN01 – TMN12

January - December mean temperatures (°C)
January - December maximum mean temperatures (°C)
January - December minimum mean temperatures (°C)

49

PPT01 – PPT12
DD_0_01 – DD_0_12
DD5_01 – DD5_12
DD_18_01 – DD_18_12
DD18_01 – DD18_12
NFFD01 – NFFD12
PAS01 – PAS12
RH01 – RH12

January - December precipitation (mm)
January - December degree-days below 0°C
January - December degree-days above 5°C
January - December degree-days below 18°C
January - December degree-days above 18°C
January - December number of frost-free days
January – December precipitation as snow (mm)
January – December relative humidity (%)

Statistical Analysis
Summary statistics of mean, median, and range for each one-year-old and twoyear-old cohort were calculated in Excel. A colonization index (CI) was also calculated
for each site’s two cohorts. The CI was calculated by multiplying the incidence and
severity in order to reach one number to represent the level of disease at that site for each
cohort. While severity alone is commonly used as the measure for disease, it does not
take into account varying levels of incidence. Since most Douglas-fir needles have SNC,
incidence is commonly rated at 1 (as opposed to 0 for no visible pseudothecia); however,
a site may have some needles that don’t exhibit signs of the disease. This is an important
piece of information that should be factored into the overall disease measure, which the
colonization index does.
Starting with separated cohorts, the percentage of needles with visible
pseudothecia (incidence, n = 10) was multiplied by the average proportion of stomata
occluded (pseudothecial density, n = 10) for the initial CI. Initial CI was then normalized
within each cohort by taking the maximum CI value and calculating all other values as a
percentage of that maximum.

50

Correlation analysis between CI and climate variables was conducted on the 2012
needle survey data, consisting of 70 sample sites. Appropriate data from Climate WNA
was not available for the 2015 collection season. The one-year-old needles collected in
2015 needed climate data from March-December 2014 and January-February 2015,
however Climate WNA did not yet have downscaled PRISM data from 2015.
Statistical analysis was performed with the software, JMP Pro 12.1.0 64-bit (SAS
Institute Inc. 2015). CI values were tested for normality by examining the distribution
with a Shapiro Wilk W test for goodness-of-fit. Pearson correlation coefficients were
calculated for CI and monthly, seasonal, and annual climate variables. Finally, linear
regressions were run to test different combinations of variables as well as with models
found in previous research for comparison.
Results
Direct quantification of SNC severity
Results from the 2015 SNC ground survey indicate that the average colonization
index (CI) is 5.3 in one-year-old needles and 22.5 in two-year-old needles. The disease
was present at all 47 sites sampled, reinforcing the ubiquitous nature of Phaeocryptopus
gaeumannii. There was strong correlation (r = 0.70) between the two cohorts, as
expected. The sites sampled throughout western Washington also showed a considerable
range in disease levels (Fig. 11). One-year-old CI values showed a weak normal
distribution after a square root transformation while two-year-old CI values were
normally distributed (Fig. 12). Based on this normal distribution plus the fact that twoyear-old needles are a better indicator of disease and typically show a stronger correlation

51

with climate data (Stone, personal communication 2015), this cohort was primarily used
in the subsequent climate analysis.

Figure 11. SNC colonization index by site sampled in the spring of 2015 in western Washington.
One-year-old needle values ranged from 0.0 to 28.5 and two-year-old needle values ranged from
3.8 to 48.2.

52

(a)

(b)

Figure 12. Distribution of normalized CI values for (a) one-year-old needles after square root
transformation (Prob<W 0.1202) and (b) two-year-old needles (Prob<W 0.5613).

In both cohorts, this represents an increase since the 2012 survey (Tables 2 and 3).
Severity has more steadily increased in one-year-old needles, with a decrease in twoyear-old needles from 2011 to 2012. The disease appears to be worse in 2015 than in
either year previously surveyed (Fig. 13). The colonization index does dampen the
extremes of severity that can be seen when observing only percentage of stomata
occluded without factoring in lower levels of incidence. Severity by percent occlusion
shows high values of 48.1 for one-year-old needles and 69.8 for two-year-old needles.

Table 2. Summary statistics of colonization index for one-year-old needles.

One-Year-Old Colonization Index
2011
2012

2015

Average

1.7

3.3

5.3

Median

1.2

2.6

3.8

Low

0.0

0.0

0.0

High

7.4

29.3

28.5

53

Table 3. Summary statistics of colonization index for two-year-old needles.

Two-Year-Old Colonization Index
2011
2012

2015

Average

20.2

15.8

22.5

Median

20.0

15.6

22.45

Low

5.0

1.2

3.8

High

39.8

32.5

48.2

Average Colonization Index

25
20
15
1yo

10

2yo
5
0
2011

2012

2015

Year Sampled

Figure 13. The trend in colonization index over the years of ground surveying in Washington:
2011, 2012, and 2015.

Disease levels may increase and/or decrease from year to year, but the relative
ranking of sites by severity should be consistent. This is due to geographic and climate
conditions at each site remaining the same. However, the three years of surveys in

54

Washington do not show this consistency in the 19 sites that were sampled each year
(Figs. 14 and 15).

Variation in Site Severity

2015 1 yo
2012 1 yo

Severity (% stomata occluded)

0.45

2011 1 yo

0.4

2015 2 yo

0.35

2012 2 yo

0.3

2011 2 yo

0.25
0.2
0.15
0.1
0.05
0
1

2

4

10 11 13 14 15 17 23 24 32 33 37 39 40 42 43 49
Site

Figure 14. Variation in site severity across the 19 sites that were sampled during all three surveys
(2011, 2012, and 2015).

55

Site Ranking by Two-Year-Old Needles
20

2
4
10

18

11

16

13
14

14

Ranking

1

15

12

17
23

10

24

8

32
33

6

37

4

39
40

2

42

0

43

2011

2012

2015

49

Figure 15. Ranking of site severity by two-year-old needles over the three years of surveying in
Washington.

These survey sites are all within the Sitka spruce zone of coastal Washington (Fig.
16). As Douglas-fir is not the naturally dominant species in this area, monoculture
plantations are a significant deviation from historical conditions. This research is not an
experiment comparing SNC inside and outside the Picea sitchensis (PISI) zone;
therefore, conclusions cannot be drawn regarding this effect, but it is an interesting part
of the story.

56

Figure 16. Map of 2015 ground survey sites over Sitka spruce forest zone.

Testing for correlation between disease severity and climate
No correlation was found between CI values and climate variables produced by
Climate WNA (Table 4). CI values were used for one-year-old, two-year-old, and
combined cohorts. Climate variables included those at the monthly, seasonal, and annual
scale. Various combinations of variables were also tested in multiple linear regressions
with no significant R2 values. To make comparisons with previous studies, CI was
plotted with average winter temperature and showed an extremely low R2 value (Fig. 17).
57

Additionally, in the one-year-old needles there was a small positive relationship while the
two-year-old needles show a small negative relationship.

Table 4. Pearson correlation coefficient values between 2012 two-year-old CI and seasonal
climate variables. Monthly and annual variables were also tested for and showed similar results.
CI
Tmax_wt
Tmax_sp
Tmax_sm
Tmax_at
Tmin_wt
Tmin_sp
Tmin_sm
Tmin_at
Tave_wt
Tave_sp
Tave_sm
Tave_at
PPT_wt
PPT_sp
PPT_sm
PPT_at

-0.0253
0.1032
0.1332
-0.0252
-0.1302
0.0380
0.0895
-0.0926
-0.0861
0.1272
0.1819
-0.0540
-0.0739
-0.0762
0.0364
-0.1584

CI
DD_0_wt
DD_0_sp
DD_0_sm
DD_0_at
DD5_wt
DD5_sp
DD5_sm
DD5_at
DD_18_wt
DD_18_sp
DD_18_sm
DD_18_at
DD18_wt
DD18_sp
DD18_sm
DD18_at

0.0966
-0.0563
0.0000
0.1522
-0.0806
0.1360
0.1771
-0.0408
0.0906
-0.1231
-0.1702
0.0822
-0.1132
0.1446
0.1718
0.0672

CI
NFFD_wt
NFFD_sp
NFFD_sm
NFFD_at
PAS_wt
PAS_sp
PAS_sm
PAS_at
RH_wt
RH_sp
RH_sm
RH_at

-0.1363
0.0463
0.0940
-0.0745
0.0931
-0.1313
-0.0867
-.0313
-0.0354
-0.0603
-0.0811
-0.0237

58

(a)

(b)

Figure 17. Relationship between colonization index (CI) and average winter temperature for (a)
one-year-old needles (R2 = 0.0008) and (b) two-year-old needles (R2 = 0.007).

59

Very little range was predicted in CI values based on average winter temperature,
although actual values varied significantly more (Fig. 18). Data sets from different years
and different cohorts showed similar results. Additionally, removing the most severely
diseased sites did not improve the correlation. In geographic terms, there does not appear
to be any particular location in which high levels of disease were focused. The varying
levels of severity appear to be evenly distributed throughout western Washington (Fig.
19).

Figure 18. Relationship between actual and predicted colonization index based on average winter
temperature for two-year-old needles sampled in 2012.

60

Figure 19. 2012 ground survey sites categorized by colonization index level.

61

Discussion
Direct quantification of SNC severity
Washington State has not had consistent ground surveying of SNC; however, a
trend of gradual increase in disease severity since 2011 is clear. This parallels what is
seen in aerial surveys which have found geographic spread to be increasing, as well. The
Olympic Mountains are constraining the disease within the western portion of the
Olympic Peninsula, but the lowlands in southwestern Washington are seeing an eastward
spread of the disease. The total acreage reported with SNC symptoms increased by 53%
between 2012 and 2015, which is significant in itself, but the acreage showing severe
symptoms increased 184.9% (49.2% for moderate symptoms). While aerial surveys only
represent estimates, it does indicate some level of increase in severity that corroborates
the pseudothecia counts.
The high values of percent stomata occluded (48.1% and 69.8% for one- and twoyear-old needles, respectively) are alarming when compared to previous research that has
shown the greatest proportion of occluded stomata on attached needles was seldom above
50% (Hansen et al. 2000). Trees heavily affected by SNC rarely hold onto more than two
years’ worth of needles because, at that point, pseudothecia are sufficiently reducing
stomatal conductance and CO2 fixation to the point that the needles are carbon sinks
instead of sources, so the needle falls off (Cannell and Morgan 1990, Manter et al.
2003a). From past research, it typically takes two years for needles to reach a 50% level
of occlusion; however, in this study, some needles were already reaching that point in
their first year. Although the average is not close to 50%, it is significant that some
needles are reaching such a high level of severity so quickly. In all years surveyed, two62

year-old needles were found to be far above the 50% threshold, reaching a high of 79% in
2011, 65.4% in 2012, and 70% in 2015.
The beginning of the frost-free period has gotten significantly earlier over the
course of the climate data used in this analysis. In 2009, the beginning of the frost-free
period occurred on April 21st while in 2015, the frost-free period began on March 27th.
As temperatures increase, budburst is occurring earlier causing WA DNR to move up the
date of their aerial survey in 2015 to compensate for this change. Harrington and Gould
(2015) projected Douglas-fir budburst to occur up to more than 60 days earlier by 2080.
This change in Douglas-fir phenology is a benefit to P. gaeumannii as it allows more
time to infect needles to higher levels.
Although it was not the focus of this study, foliage retention was estimated during
the ground surveys to collect needle samples. Needle retention was quite low in the
second cohort, with an average of 7.4 in 2012 and 6.9 in 2015. These low foliar retention
rates in combination with the high levels of severity suggest that the disease may be
having greater impacts in Washington State than in Oregon. Decreased foliage retention
could also bias CI values, in that the most heavily infected needles have already abscised
by the time of sampling so disease severity is estimated at lower levels than reality.
When looking at the nineteen sites sampled each of the three years, increases and
decreases of severity are not consistent across the sites. It is clear that site severity is
quite dynamic when looking at a line graph of site ranking. Monitoring in Oregon since
1996 has found a fairly constant ranking of sites, leading to the existing paradigm that

63

site-related factors determine severity (Hansen et al. 2000). However, the sites in
Washington do not appear to follow this.
Testing for correlation between disease severity and climate
Boyce (1940) suggested that seasonal patterns in local climate might affect fungal
growth in different ways, so it was expected to find similar or perhaps only slightly
different correlation results than found in previous studies. The similarity of models for
Oregon (Manter et al. 2005) and New Zealand (Stone et al. 2007a) suggests that winter
temperature does indeed explain disease severity variation (Fig. 20). Both studies
showed a strong relationship between the two variables (R2 = 0.847 in Manter et al. 2005
and R2 = 0.75 in Stone et al. 2007a). However, this study in Washington State found no
correlation between colonization index and any climate variables at the monthly,
seasonal, or annual scale.

64

Figure 20. Relationship between colonization index and winter temperature in (a) New Zealand,
where June is during the winter, R2 = 0.75 for both (top) one-year-old and (bottom) two-year-old
needles and (b) Oregon, where the relationship varied by year sampled but still showed a strong
relationship in both (top) one-year-old and (bottom) two-year-old needles. From Stone et al.
2007a and Manter et al. 2005.

Regression showing actual CI by predicted CI shows much more variation in
levels of disease actually seen than what was predicted by average winter temperature.
Other variables showed a nearly identical graph. This minimal range in predicted values
indicates that some other factor is influencing actual levels of disease outside the climate
variables for which this study tested.
The sites sampled in Washington do not have a very large range in average winter
temperature; only 2.1 to 5.3° C. In contrast, Manter et al. (2005) had a winter
temperature range of approximately 4 to 9° C across only 9 sites while Stone et al. (2007)

65

winter temperatures ranged from approximately 3 to 7.5° C across 16 sites. Perhaps with
more sites or a smaller range in temperature the correlation wouldn’t be so strong.
In an ecological context, having Douglas-fir plantations covering a large amount
of the Sitka spruce vegetation zone cannot be ignored as an influencing factor in the
spread of SNC. The timber industry has primarily been replanting Douglas-fir trees
following harvest for approximately 80 years resulting in an increasing amount of
potential hosts for P. gaeumannii. More hosts mean more inoculum available for future
years of infection allowing the cycle to feed itself.
Conclusion
While climate is likely playing some role in the increase in SNC severity and
spread, this relationship is not clearly defined. Some studies have found a simple, strong
relationship, but the data in Washington State indicates that a higher level of complexity
in disease behavior is occurring. Due to uncertainties in how climate affects the disease
and how climate change will likely bring new factors into play, it is difficult to predict
the future of the SNC epidemic.
As these environmental factors play out, we as forest pathologists can observe and
increase our understanding of the disease. Controlling the disease, however, is unlikely.
In the meantime, perhaps the most practical action to be taken is to manage forests as
responsibly as possible, even if that means planting less Douglas-fir in the coastal forest
of western Washington.

66

67

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Appendix A - Site conditions from the 2012 ground survey

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