An Abstract of the Thesis Of

AN ABSTRACT OF THE THESIS OF

Lilah Gonen for the degree of Master of Science in Botany and Plant Pathology presented on December 9, 2020.

Title: Community Ecology of Foliar Fungi and Oomycetes of Pseudotsuga menziesii on the Pacific Northwest Coast.

Abstract approved: ______Andy Jones Jared LeBoldus

Pseudotsuga menziesii var. menziesii (coast Douglas-fir) is a tree of ecological, economic, and cultural value in its native North American Pacific

Northwest (PNW) distribution. P. menziesii is host to a variety of well- documented endophytic foliar microorganisms, including the fungus

Nothophaeocryptopus gaeumannii, the causal agent of Swiss needle cast (SNC), and the oomycete Phytophthora pluvialis, which causes cryptic disease symptoms in P. menziesii. Little is understood about how entire foliar microbial communities are structured by geography, climate, and host lineage, nor how foliar fungi and oomycetes interact at the tree level. This study used a large-scale reciprocal transplant experiment, next-generation sequencing (NGS), and culture-based methods to characterize the diversity and structure of foliar fungi and oomycetes of P. menziesii across three sites on the PNW coast. Fungal community composition within trees was structured by host location (p = 1e-4,

1.5e-3) as well as interactions between host location and lineage (p = 0.02, 6.4e-

3, 8e-4). Oomycete communities were dominated by a single OTU, assigned to

Phytophthora cacuminis, a recently described species in Australia. An undescribed Pythium species was isolated in culture from 18 trees throughout the study sites. Generalized linear mixed models revealed that fungal community richness was positively correlated to oomycete community richness among trees

(estimated coefficient = 0.14, p = 8.3e-16), and that presence of P. cacuminis negatively predicted presence of N. gaeumannii (estimated coefficient = -0.65, p

= 0.03). This raises questions about P. cacuminis’ presence and origins in the

PNW as well as its effects on tree health. This study is among the first to use NGS to describe P. menziesii’s foliar fungal community and to characterize nonpathogenic oomycetes residing in P. menziesii needle tissue. It illustrates the need for further experimental research to identify biotic drivers of microbial community assembly, as well as the downstream implications for forest management.

Community Ecology of Foliar Fungi and Oomycetes of Pseudotsuga menziesii on the Pacific Northwest Coast

by Lilah Gonen

A THESIS

submitted to

Oregon State University

in partial fulfillment of the requirements for the degree of

Master of Science

Presented December 9, 2020 Commencement June 2021

Master of Science thesis of Lilah Gonen presented on December 9, 2020

APPROVED:

Major Professor, representing Botany and Plant Pathology

Head of the Department of Botany and Plant Pathology

Dean of the Graduate School

I understand that my thesis will become part of the permanent collection of Oregon State University libraries. My signature below authorizes release of my thesis to any reader upon request.

Lilah Gonen, Author

ACKNOWLEDGEMENTS

First, I must thank my advisors and committee: Jared LeBoldus, Andy

Jones, Posy Busby, and Dave Shaw for your mentorship, patience, respect, and, importantly, funding of my time and energy at OSU. I feel very lucky to now have the intellectual foundations of both a forest ecologist and pathologist and I do believe I’ll take the diversity of thought and methodology that these four have instilled in me far into my career.

Second, to the lab members who offered me so much in my two plus years at OSU. Chiefly, Kelsey Søndreli, for keeping the lab clean and functional, ordering most of my equipment, and patiently helping with virtually all of my laboratory tasks; Patrick Bennett, for going on an overnight sampling trip with me to Washington, driving the whole way, and keeping a good attitude despite falling a lot; Devin Leopold, for your instrumental help in bioinformatics; Paul

Reeser and Wendy Sutton, for being some of the best resources in the world

(truly) on oomycete biology, culturing, and sequencing; Kyle Gervers, for your enthusiasm in all things microbiome, and your involvement in everything from sampling trips to troubleshooting library prep to diving deeply into ecological theory; Kayla Delventhal for the statistical breakthroughs, commiseration, and friendship; Javier Tabima, for teaching me many things including how to write a manuscript, how to use the cluster, and how to ask stupid questions; and finally

Shawn McMurtrey, for washing all of our dishes and making me laugh.

Third, to the US Forest Service for granting me access to the SSMT sites, assisting me in the field, and sharing valuable data with me. Those folks include Brad St. Clair, Connie Harrington, Chris Poklemba, Beverly Luke, Leslie Brody, and Dave Thornton.

Fourth, to the lifelong friendships I made at Shrub House: Kat, Cedar, Meredith, and Allie.

Fifth, to Lauren, Livi, and dear Gordon, for the important stuff.

And finally, a profound acknowledgement to the Kalapuya people and the Confederated Tribes of the Grand Ronde and Siletz, on whose stolen land I was raised and OSU sits.

TABLE OF CONTENTS Page

1. General Introduction ...... 1

1.1 Literature Cited ...... 12

2. Community Ecology of Foliar Fungi and Oomycetes of Pseudotsuga menziesii on the Pacific Northwest Coast ...... 20

2.1 Abstract ...... 21

2.2 Introduction ...... 22

2.3 Materials and methods...... 28

2.3.1 Study sites ...... 28

2.3.2 Sample collection...... 29

2.3.3 Culturing and sequencing oomycetes ...... 30

2.3.4 Sequencing fungal and oomycete communities ...... 33

2.3.5 Bioinformatics ...... 35

2.3.6 Statistical analysis ...... 37

2.4 Results ...... 40

2.4.1 Oomycete isolates ...... 40

2.4.2 Community composition of fungi and oomycetes ...... 41

TABLE OF CONTENTS (Continued)

2.4.3 Fungal diversity in response to biotic and abiotic predictors .....43

2.5 Discussion ...... 45

2.5.1 Foliar fungal communities are structured by local environmental

conditions ...... 45

2.5.2 Foliar oomycete communities are dominated by one OTU...... 50

2.5.3 Presence of foliar fungi can be predicted by the presence of foliar

oomycetes ...... 52

2.6 Conclusions ...... 54

2.7 Literature Cited ...... 57

2.8 Figures ...... 67

2.9 Tables ...... 82

3. General Conclusions ...... 86

3.1 Literature Cited ...... 92

4. Bibliography ...... 96

LIST OF FIGURES

Figure Page

2.1 Locations of seed source region (SSR) (left) and study sites (right). Seed was collected from 2 maternal trees (inset) in each of 5 locations within each SSR. Each SSR was composed of 10 lines of half-siblings (families). Adapted from Wilhelmi et al. (2017)...... 67

2.2 Example of study site layout. Each site was divided into 4 blocks, where each SSR was randomly assigned a plot. Each SSR plot contained 2 replicates of the 10 families. 5 families were randomly selected for sampling, making a total of 10 samples per SSR plot (inset)...... 68

2.3 Example of needles selected for culturing and DNA extraction. Only cast needles with living green tissue were selected ...... 69

2.4 A) 10 needles from a sample plated in CARP. B) Pythium mycelia emerging from a needle plated in CARP...... 70

2.5 Pythium mycelia growing in cornmeal agar ...... 71

2.6 Microscopic image at 100x magnification of Pythium mycelia and reproductive structures. Oogonia with attached antheridia (circled in red) indicate the presence of a homothallic species ...... 72

2.7 Bar graph of the proportion of doubleton, tripleton, etc. OTUs present in the oomycete dataset. Over 50% of OTUs appeared in 2 or 3 samples. One OTU, assigned to P. cacuminis appeared in the overwhelming majority of samples (173 out of 181) and was therefore the only oomycete OTU considered in downstream analyses ...... 73

2.8 ML trees of Pythium isolate genes aligned to corresponding databases. A) COI; B) ITS; and C) rps10. Isolates are circled in red and known pathogens of P. menziesii seedlings are indicated with blue arrows ...... 74

LIST OF FIGURES (Continued)

2.9 Heatmap of all fungal OTUs assigned to a taxonomic group across all three sites. Node width and color indicate log proportional abundance of sequence reads assigned to a given taxonomic group. Dothideomycetes and Leotiomycetes within Ascomycota were the most commonly observed taxonomic groups ...... 77

2.10 Distance-based redundancy analysis (db-RDA) ordination of foliar fungal communities constrained by site based on Bray-Curtis dissimilarity. Each point represents the fungal community of a single tree’s pooled needles. Axes scores show the percentage of total cumulative variation explained by that axis, for a total of about 11.3% ...... 78

2.11 Boxplots of log relative abundance of significant indicator OTUs (Indicator Value ≥ 0.3, BH p ≤ 0.05) at each site. Jammer had one unique indicator OTU, OTU 8, assigned to Penicillium penicillioides...... 79

2.12 Boxplots of Chao rarefied richness estimates of A) fungal OTUs by site; and B) fungal OTUs by SSR; and log-transformed Chao rarefied richness estimates of C) oomycete OTUs by site; and D) oomycete OTUs by SSR. Fungal richness was significantly different (Dunn’s test of Kruskal Wallace rank sums) between all three sites, and oomycete richness was significantly lower at Jammer compared to Nortons and Floras. SSR did not appear to confer any significant difference in OTU richness among fungi or oomycetes ...... 80

2.13 Venn diagram of N. gaeumannii and P. cacuminis presence in samples. 139 out of 282 samples (49%) exclusively contained one OTU or the other ...... 81

LIST OF TABLES

Table Page

2.1 Primers used in gene amplification. A) Amplicon primers for oomycete isolate sequencing; and B) amplicon primers, Illumina adapters, and heterogeneity spacers used for Illumina sequencing of fungal and oomycete communities ...... 82

2.2 Oomycete isolates collected and sequenced from the SSMT sites. Some isolates were lost to contamination or failed to grow in liquid media and were not sequenced ...... 83

2.3 PERMANOVA results of location and host lineage effects on fungal communities, measured as Bray-Curtis dissimilarity. Location effects: Site, Block nested in Site. Host lineage effects: SSR, Family nested in SSR. The highest order term (Block[Site] x SSR[Family]) was excluded because it lacked replication at the lowest level due to dead or missing trees throughout the sites ...... 83

2.4 Indicator values, Benjamini-Hochberg adjusted p-values, and assigned taxonomic groups of indicator OTUs in each site. Only OTUs with indicator values ≥ 0.3 and p ≤ 0.05 were reported (Dufrêne and Legendre 1997)...... 84

2.5 Model selection table of four generalized linear mixed models with fungi richness as response. Random effects: Site, Block(Site), SSR, Family(SSR). The richness model, with AICc weight = 0.83, is the only model to fall within a 95% confidence interval (Zuur et al. 2009) ...... 84

2.6 Output of mixed-effect logistic regression of P. gaeumannii presence/absence as response. Random effects: Site, Block(Site). SSR and Family(SSR) were omitted as random effects because models failed to converge when they were included ...... 85

Chapter 1: General Introduction

Spanning from southern Alaska to northern California (CA), temperate forests are an important and widespread biome in the Pacific Northwest (PNW) of

North America. Nearly half of the state of Oregon (OR), or over 12 million hectares

(30 million acres) is forestland (OFRI 2019a). PNW temperate forests are largely dominated by highly productive, long-lived coniferous trees (Waring and Franklin

1979), who thrive in the mild temperatures and high rainfall that is characteristic of the region between the Pacific coast and the Cascade Range crest (Franklin and

Donato 2020). These forests offer valuable ecosystem services such as sequestration of atmospheric carbon (Bastien 2019), habitat structure (Anthony et al. 1982, Olson et al. 2007, Carroll et al. 2010), cultural value (Pojar and MacKinnon 1994), and economic benefits such as timber revenue (OFRI 2019b), wages (OFRI 2019b), and the harvest of non-timber forest products (Pilz and Molina 2002). In terms of both biomass and timber production, Pseudotsuga menziesii (Mirb.) Franco var. menziesii

(coast Douglas-fir) is the most dominant tree in these forests.

Pseudotsuga menziesii is a long-lived coniferous tree native to the PNW

(Pojar and MacKinnon 1994). It is one of the most ecologically and economically important tree species in the PNW, covering nearly 20 million hectares of land

(Spiecker et al. 2019). Its old growth forests serve as critical habitat for endangered species, and its highly productive plantations are the cornerstone for the PNW’s timber industry (Howe et al. 2013) In 2013, P. menziesii made up about 70% of OR’s total timber harvest stock (Simmons et al. 2019), an industry that generated over 2

$18 billion in output in 2016 (OFRI 2019b). Pseudotsuga menziesii has also been introduced to other temperate regions around the globe such as Europe, New

Zealand (NZ), and Argentina where it’s grown for timber production (Hermann and

Lavender 1999).

Pseudotsuga menziesii is host to a variety of pathogens in the PNW that can cause root, stem, and foliar diseases, as well as damping off in seedlings. These pathogens include Armillaria ostoyae (Romagn.) Herink (Armillaria root disease)

(Bloomberg 1989, Baleshta et al. 2005), Coniferiporia sulphurascens (Pilat) L.W.

Zhou & Y.C. Dai (laminated root rot) (Bloomberg and Reynolds 1985), and

Leptographium wageneri (W.B. Kendr.) M.J. Wingf. (black stain disease) (Harrington and Cobb 1987). Foliar diseases have been particularly harmful to P. menziesii growth and survival on the PNW coast in recent decades (Shaw et al. 2011). Swiss needle cast (SNC) is a prominent foliar disease of P. menziesii, and is caused by

Nothophaeocryptopus gaeumannii (T. Rhode), a fungus endemic to the region (Boyce

1940). Described in the 1920s in response to significant losses in nonnative

European P. menziesii plantations, N. gaeumannii was originally considered a benign and ubiquitous fungal associate of P. menziesii that only caused disease in exotic environments (Boyce 1940). Symptoms of SNC began appearing in managed P. menziesii forests in the coastal PNW in the 1980s and 1990s (Hansen et al. 2000,

Shaw et al. 2011). The disease has since erupted in the region, increasing from about

50,000 ha of affected forestland in 1996 to over 200,000 ha in 2015 in OR alone

(Ritóková et al. 2016). In the most severely affected stands, P. menziesii’s radial growth can be reduced by as much as 85% (Black et al. 2010), and height by up to

52% (Maguire et al. 2002). SNC is a serious threat to P. menziesii’s critical ecosystem services.

Nothophaeocryptopus gaeumannii infects P. menziesii foliar tissue through needle stomata, where it colonizes the intercellular spaces (Stone et al. 2008a). SNC symptoms occur when N. gaeumannii fruiting bodies (pseudothecia) emerge from

stomata, occluding them and limiting the CO2 assimilation and transpiration needed for photosynthesis (Manter et al. 2000, Manter and Kavanagh 2003). Affected needles are prematurely abscised (Manter et al. 2000). Severely diseased trees display obviously chlorotic needles, thin crowns from premature needle loss, and abundant, visible fruiting of N. gaeumannii on 1- and 2-year-old needles (Hansen et al. 2000). These symptoms are directly associated with reductions in overall growth

(Maguire et al. 2002).

Though SNC has emerged on the PNW coast in recent years, N. gaeumannii does not always cause disease. Pseudothecia have been observed on P. menziesii needles sampled throughout the PNW coast, but SNC disease severity is variable throughout the region (Ritóková et al. 2016). Severity appears to be tightly correlated to the proportion of stomata occluded on a needle (Manter and Kavanagh

2003), although some trees have exhibited high stomatal occlusion with little disease expression (Temel et al. 2004). Prior to the 1980s, SNC was not considered to be a relevant disease in the PNW, despite being found virtually anywhere P. menziesii was present (Boyce 1940). Nothophaeocryptopus gaeumannii can therefore be considered an endophytic fungus with latent pathogenicity.

Endophytes, microorganisms that can occupy plant tissue while causing no apparent effect to the host (Petrini 1991, Arnold 2007, Rodriguez et al. 2009), can behave as latent pathogens or saprophytes, causing disease or decomposing plant tissue as the host ages or environmental conditions change (Stone 1987, Boddy 2001, Boberg et al. 2011, U’Ren and Arnold 2016).

Because SNC is a relatively recent problem with ancient origins, many have hypothesized that its emergence and sustained severity in the PNW can be explained by changes in management and climate. The SNC epidemic area in the

PNW approximately corresponds to the Picea sitchensis (Bong.) Carr (Sitka spruce) vegetation zone, a narrow strip of coastal forest that is defined by its close proximity to the Pacific Ocean, moderate climate and the historic dominance of P. sitchensis and Tsuga heterophylla (Raf.) Sarg. (western hemlock) (Stone et al. 2008b, Ritóková et al. 2016). In naturally occurring forests P. menziesii occurs as an intermediate tree within a diverse forest canopy. Commercial forestry in the area has replaced these historically diverse forests with pure stands of economically preferred P. menziesii, potentially exposing this tree to environmental conditions that promote N. gaeumannii pathogenicity (Stone et al. 2008b). In this case, SNC could be an example of a density-dependent disease that has been managed into existence (Freckleton and Lewis 2006, Johnson et al. 2012).

The climatic conditions of the P. sitchensis zone and changes in annual weather patterns due to global climate change have been strongly associated with

SNC disease severity in the PNW. In climate modeling studies, the strongest

predictors of disease severity have been high winter temperatures (Manter et al.

2005, Stone et al. 2008b, Lee et al. 2017), high spring leaf wetness (Manter et al.

2005), and high summer precipitation (Hood 1982, Lee et al. 2017). Average temperatures in the PNW have increased by approximately 0.8°C throughout the

20th century, with the largest changes occurring in winter months (Mote et al. 1999), and temperatures are expected to keep rising in the 21st century (Pachauri et al.

2015).

The genetic lineage of the host may also play a role in a tree’s expression of disease. Some efforts have been made to breed P. menziesii with high tolerance or resistance to SNC, with varying success (Jayawickrama et al. 2012). However, tolerance or resistance to SNC is not visible when improved trees are planted in regions with high disease pressure, such as the area around Tillamook, OR (Kastner et al. 2001). Greater susceptibility has been observed in P. menziesii populations from inland areas with low winter temperatures and precipitation (Hood 1982).

Climate transfer distances, or the difference in climate between a tree’s seed source and where the tree is grown, have been correlated with SNC disease severity

(Wilhelmi et al. 2017). This indicates that while host lineage alone may not have strong relationships to N. gaeumannii presence and abundance, the local environment of the tree as well as the interactions between its local environment and origin may be useful predictors. As global climates continue to warm (Pachauri et al. 2015), the assisted migration of trees to more suitable environments is a viable option for conserving forest ecosystems and producing timber in the PNW (St. Clair and Howe 2007, Ste-Marie et al. 2011). Understanding how that movement may

affect P. menziesii’s foliar microbial community composition is essential for understanding forest health and disease management into the future.

Finally, presence, relative abundance, and diversity of other microorganisms in P. menziesii needle tissue may correlate to the presence of N. gaeumannii and impact it has on its host. A number of other foliar fungal pathogens, saprophytes, and endophytes have been observed and described in P. menziesii (Parker and Reid

1969, Bernstein and Carroll 1977, Carroll and Carroll 1978, Sherwood-Pike et al.

1986, Daniels et al. 2018), but rarely with an aim of understanding community dynamics. Daniels et al. (2018) found that foliar fungal endophyte communities were structured both by a tree’s seed source region and planting location. However, their analysis relied on culture-based methods on a single media type rather than sequencing approaches, and therefore likely did not represent the true extent of diversity present (Lindahl et al. 2013).

One microorganism that has been shown to coexist and possibly compete with N. gaeumannii in P. menziesii foliage is the oomycete Phytophthora pluvialis

Reeser, Sutton, & Hansen. Oomycetes are organisms in the diverse kingdom

Straminipila, which also includes brown algae and diatoms. Despite their genetic distance, oomycetes share some convergent traits with fungi, such as mycelial growth, sporulation, and plant pathogenicity. Most of the scientific interest in oomycetes has historically revolved around their roles as plant pathogens, with over

60% of known species classified as such (Thines and Kamoun 2010). This is for good reason: oomycete pathogens are responsible for untold economic, ecological,

and cultural losses. For example, the introduction of Phytophthora infestans

(Montagne) de Bary to Europe from Mexico destroyed Ireland’s potato crops in the

19th century, caused the Irish Potato Famine, and facilitated the Irish diaspora (Goss et al. 2014). Phytophthora ramorum Werres, De Cock & Mann in’t Veld is an invasive pathogen and the cause of sudden oak death in northern CA and southern OR (Rizzo et al. 2002). Sudden oak death has led to the rapid decline of Notholithocarpus densiflorus (Hook. & Arn.) Manos, Cannon, & Oh (tanoak) and Quercus agrifolia Née

(coast live oak) in the region, fundamentally altering forest habitat structure (Cobb et al. 2012). Many Pythium species are responsible for damping off of forest nursery seedlings and are considered some of the most important soilborne pathogens in the PNW’s commercial timber industry (Dumroese and James 2005, Weiland et al.

2013). Despite oomycetes’ importance as plant pathogens, little is understood about their roles as saprophytes and endophytes in natural and commercial forests (Choi et al. 2015).

Phytophthora pluvialis is the causal agent of red needle cast, a significant foliar disease of Pinus radiata D. Don (radiata pine) in NZ (Dick et al. 2014). P. pluvialis was first isolated from baited streams, soils, and canopy drip in P. menziesii/N. densiflorus forests in southwestern OR (Reeser 2013, Hansen et al.

2017). P. pluvialis has since been isolated from symptomatic and asymptomatic P. menziesii foliage both in the PNW and NZ, but with more inconsistent and cryptic symptoms than on P. radiata (Hansen et al. 2015, Gómez-Gallego et al. 2019, Tabima et al. 2020). In the PNW, episodic and geographically constrained needle casting events in P. menziesii have been tied to P. pluvialis (Hansen et al. 2017), suggesting

that its severity in P. menziesii is limited to certain environmental conditions

(Tabima et al. 2020). Phylogenetic analyses have revealed that P. pluvialis likely migrated from the PNW to NZ (Brar et al. 2018, Tabima et al. 2020). The significant shift in host appeared to have changed its functional role from cryptic, facultative pathogen and commensal endophyte to the causal agent of a significant disease of a nonnative tree.

Phytophthora pluvialis and N. gaeumannii coinfect P. menziesii foliage in the

PNW and NZ (Gómez-Gallego et al. 2019) as well as in vitro (Gómez-Gallego et al.

2017). In the PNW, the relative abundances of both microorganisms are negatively correlated when observed in the same tree (Gómez-Gallego et al. 2019). Needle stomata are the primary mode of colonization and reproduction for both N. gaeumannii and P. pluvialis (Dick et al. 2014, Gómez-Gallego et al. 2019), and both N. gaeumannii pseudothecia and P. pluvialis asexual fruiting bodies (sporangia) have been observed emerging from stomata on the same needle (Gómez-Gallego et al.

2019). This suggests that N. gaeumannii and P. pluvialis are capable of both some degree of coexistence and competition, and could have a long history of sympatry.

While foliar fungi of P. menziesii have been catalogued in culture-based studies (Bernstein and Carroll 1977, Carroll and Carroll 1978, Daniels et al. 2018), oomycetes have not received the same level of attention. Besides P. pluvialis, P. ramorum has been found in P. menziesii foliage in CA and OR (Garbelotto et al.

2003), occasionally causing non-lethal symptoms (Garbelotto and Hayden 2012).

The wet and mild climates of PNW forests make them a fitting environment for

identifying oomycetes (Sims et al. 2015, Hansen et al. 2017, Kozanitas et al. 2017).

As P. pluvialis has shown, understanding the dynamics of even innocuous endophytes may inform forest management decisions if a microbe is detected in a new environment. Furthermore, the contrasting loads of P. pluvialis and N. gaeumannii opens questions about how N. gaeumannii responds to the presence of other oomycetes, and even how entire fungal communities may associate with their oomycete counterparts.

Foliar microbiomes can be influenced by many of the factors known to predict prolific N. gaeumannii infections: climate, location, host lineage, and the interactions between them. Foliar microbiomes of a single species have been observed to have considerable variation when sampled along elevational, latitudinal, or other significant climate gradients (Vacher et al. 2008, Terhonen et al.

2011, Millberg et al. 2015, Bowman and Arnold 2018). Geographic distance has also been shown to be a very useful predictor for foliar community structure, with the largest effects occurring at the landscape level, followed by tree-to-tree variation within sites (Zimmerman and Vitousek 2012, Cordier et al. 2012, Ibrahim et al.

2017, Barge et al. 2019). Different plant species are shown to be host to unique foliar microbial communities (Arnold and Lutzoni 2007, Solis et al. 2016), but when only one host species is observed, host lineage on its own doesn’t tend to play a large role in structuring foliar communities. Host lineage by location interactions however, have been shown to have an effect (Hoffman and Arnold 2008, Cordier et al. 2012, Wagner et al. 2016, Ibrahim et al. 2017). The fact that geographic effects tend to outweigh host effects in explaining foliar community structure is likely a

feature of spore dispersal limitation, which has been shown to structure fungal communities (Peay et al. 2012). Neighboring trees are much more likely to share inoculum than those kilometers apart, even if they belong to different genetic groups. A great number of foliar endophytic fungi have been shown to be generalists with cosmopolitan distributions across plant tissue and host species (Arnold and

Lutzoni 2007, Hoffman and Arnold 2008, Cordier et al. 2012). Within-species genetic variation of a host is less likely to deter a generalist endophyte from colonizing its leaf tissue.

Reciprocal transplant experiments are a useful way to measure community variation across different levels of geography and host lineage (Kawecki and Ebert

2004, Thiergart et al. 2019). The present study uses a large reciprocal transplant provenance study, the Douglas-fir Seed Source Movement Trial (SSMT), to address questions about how foliar fungi and oomycete communities are structured across space and host lineage. The SSMT is made up of thousands of P. menziesii trees from

12 seed source regions (SSRs) across the PNW planted at 9 corresponding sites

(Ford et al. 2016). This study makes use of three coastal SSRs in Washington State

(WA) and OR, and their corresponding coastal sites. These all fall within the observed range of P. pluvialis and other forest oomycetes (Sims et al. 2015, Hansen et al. 2017, Tabima et al. 2020). Previous studies have identified various foliar fungi in the coastal SSMT sites, including a wide diversity of endophytes (Daniels et al.

2018) and symptoms of SNC and Rhabdocline needle cast, a foliar disease caused by the fungus Rhabdocline pseudotsugae (Wilhelmi et al. 2017).

Other studies that have attempted to characterize foliar microorganisms of P. menziesii have almost exclusively focused on fungi and have relied on culture-based

(Bernstein and Carroll 1977, Carroll and Carroll 1978, Daniels et al. 2018) or symptom-based (Boyce 1940, Parker and Reid 1969, Sherwood-Pike et al. 1986,

Stone 1987, Hansen et al. 2000, Wilhelmi et al. 2017, Samek et al. 2019) approaches.

The present study applies techniques in both culturing and next-generation sequencing (NGS) to provide a more comprehensive description of P. menziesii’s foliar fungal and oomycete communities (Lindahl et al. 2013, Taylor et al. 2016,

Foster 2020). Selectively culturing oomycetes from P. menziesii needles as well as sequencing entire fungal and oomycete communities from needle tissue across a large reciprocal transplant experiment will help address the following questions:

1. What oomycetes, besides P. pluvialis, inhabit P. menziesii foliage on the PNW

coast?

2. Do fungal communities observed through an NGS lens reflect those that have

been described in previous culture-based and symptom-based studies?

3. How do these microbial communities respond to the effects of host location

and lineage?

4. Does fungal diversity respond to abiotic and biotic factors that have been

shown to influence the presence and impact of N. gaeumannii, such as climate

transfer distances and presence of oomycetes?

5. Does N. gaeumannii respond to the presence of other oomycetes similarly to

how it responds to the presence of P. pluvialis?

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Chapter 2: Community Ecology of Foliar Fungi and Oomycetes of Pseudotsuga menziesii on the Pacific Northwest Coast

Abstract

Pseudotsuga menziesii var. menziesii (coast Douglas-fir) is a tree of ecological, economic, and cultural value in its native North American Pacific Northwest (PNW) distribution. P. menziesii is host to a variety of well-documented endophytic foliar microorganisms, including the fungus Nothophaeocryptopus gaeumannii, the causal agent of Swiss needle cast (SNC), and the oomycete Phytophthora pluvialis, which causes cryptic disease symptoms in P. menziesii. Little is understood about how entire foliar microbial communities are structured by geography, climate, and host lineage, nor how foliar fungi and oomycetes interact at the tree level. This study used a large-scale reciprocal transplant experiment, next-generation sequencing

(NGS), and culture-based methods to characterize the diversity and structure of foliar fungi and oomycetes of P. menziesii across three sites on the PNW coast.

Fungal community composition within trees was structured by host location (p =

1e-4, 1.5e-3) as well as interactions between host location and lineage (p = 0.02,

6.4e-3, 8e-4). Oomycete communities were dominated by a single OTU, assigned to

Phytophthora cacuminis, a recently described species in Australia. An undescribed

Pythium species was isolated in culture from 18 trees throughout the study sites.

Generalized linear mixed models revealed that fungal community richness was positively correlated to oomycete community richness among trees (estimated coefficient = 0.14, p = 8.3e-16), and that presence of P. cacuminis negatively predicted presence of N. gaeumannii (estimated coefficient = -0.65, p = 0.03). This raises questions about P. cacuminis’ presence and origins in the PNW as well as its effects on tree health. This study is among the first to use NGS to describe P.

menziesii’s foliar fungal community and to characterize nonpathogenic oomycetes residing in P. menziesii needle tissue. It illustrates the need for further experimental research to identify biotic drivers of microbial community assembly, as well as the downstream implications for forest management.

Introduction

Pseudotsuga menziesii (Mirb.) Franco var. menziesii (Douglas-fir) is a conifer species endemic to the Pacific Northwest (PNW) of North America, where it has important ecological, economic, and cultural value. Multiple microorganisms reside within P. menziesii needle tissue, comprising various functional groups that can differentially influence their host. Endophytes occupy needle tissue while causing no apparent symptoms (Petrini 1991, Arnold 2007, Rodriguez et al. 2009). Some endophytes may play mutualistic roles by directly competing with pathogens

(Sieber 2007). Saprophytes proliferate in decaying foliar tissue and may reside in living needles as endophytes prior to abscission (Stone 1987, U’Ren and Arnold

2016). Foliar pathogens damage needle tissue, limiting gas exchange and photosynthesis, and cause reductions in tree growth (Manter et al. 2000, Maguire et al. 2002, Samek et al. 2019). Some endophytes may also be latent pathogens, colonizing needles with no apparent symptoms until conditions shift to favor pathogenicity (Manter et al. 2005, Sieber 2007). Together, these functional groups comprise a community of needle-dwelling microorganisms spanning multiple kingdoms of life.

Foliar microorganism communities can be influenced by a variety of factors, including geography, proximity to other potential hosts, and host genetic lineage.

Several studies have documented geographic variation among trees’ foliar microbial communities (Carroll and Carroll 1978, Hoffman and Arnold 2008, Zimmerman and

Vitousek 2012, Millberg et al. 2015, Bowman and Arnold 2018, Barge et al. 2019).

Millberg et al. (2015) found appreciable shifts in fungal community composition and diversity of Pinus sylvestris L. needles along a latitudinal gradient in Sweden. Barge et al. (2019) similarly observed that leaves of Populus trichocarpa (Torr. & A. Gray ex Hook.) Brayshaw trees west of the Cascade Range in the PNW hosted significantly different and more diverse fungal communities than those east of the Cascade

Range. They also found that climate explained more variation in community composition than spatial distance alone. Within a site, a tree’s foliar microbiome could be shaped by smaller-scale factors, such as variation in microclimate and proximity to alternate plant hosts (Saikkonen 2007, Hantsch et al. 2013, Nguyen et al. 2016). Dispersal limitation is known to have a role in structuring communities of spore-dependent organisms (Peay et al. 2012), suggesting that community composition could be mediated by inoculum present in neighboring hosts.

Dominant tree endophytes likely coevolved with their hosts, leading to some degree of host specificity of foliar microorganisms among different tree species

(Sieber 2007). Solis et al. (2016) observed that foliar fungal communities of tropical

Ficus species were more similar among closely related host species. The genetic identity of a host appears to have a particularly pronounced role in foliar community structure when considered in tandem with its location. Hoffman and

Arnold (2008) examined foliar fungal communities of closely related temperate

Cupressaceae species planted in their native and non-native environments. They observed that different endophyte genera dominated community assemblages of each combination of host species and location. Ibrahim et al. (2017) observed that foliar fungal communities of Fraxinus ornus L. had greater within-site variability in sites planted with trees of different cultivars, compared to sites planted with trees from a single, naturally regenerating population. And Wagner et al. (2016) reported that host genotype effects on foliar bacterial communities of the wild mustard

Boechera stricta A. Gray were strongest within study sites compared to across all study sites.

Nothophaeocryptopus gaeumannii (T. Rhode) Videira, C. Nakash, U. Braun &

Crous is an obligate fungal endophyte and latent pathogen of P. menziesii. It is the causal agent of the foliar disease Swiss needle cast (SNC) (Boyce 1940). SNC is widespread across hundreds of thousands of hectares in coastal PNW (Ritóková et al. 2016), primarily causing extensive damage in commercially managed forests.

SNC leads to considerable reductions in growth and economic output (Maguire et al.

2002, Shaw et al. 2011). N. gaeumannii colonizes live needles through their stomata without eliciting a host response (Stone et al. 2008). SNC occurs when a critical number of stomata are occluded by the fungus’ pseudothecia (fruiting bodies), limiting carbon uptake (Manter et al. 2000). This causes needles to become chlorotic and drop from the tree (Manter et al. 2000), thinning the canopy, reducing photosynthetic capacity, leading to further stress and potentially tree death.

N. gaeumannii is ubiquitous wherever the P. menziesii grows and does not always cause symptoms in its host (Boyce 1940, Ritóková et al. 2016, Wilhelmi et al.

2017). The conditions that have been found to predict SNC disease severity are largely climactic as well as specific to host by location interactions. Manter et al.

(2005) observed that the abundance of pseudothecia on needles was most correlated with winter mean daily temperature and spring cumulative leaf wetness.

In using tree ring width chronologies to reconstruct SNC history in PNW P. menziesii forests, Lee et al. (2017) found that growth impact from SNC was strongly correlated to high winter and low summer temperatures, and high spring precipitation. Climate transfer distances, or the difference in climate between a plant’s seed source and where the plant is grown, have also been observed to predict symptoms and severity of SNC (Wilhelmi et al. 2017). Mean summer precipitation (MSP), mean winter temperature (MWT) and continentality (TD) transfer distances have been shown to be strong predictors of SNC infection, crown density, crown color, and needle retention (Wilhelmi et al. 2017). The predictive power of climate transfer distances in SNC severity suggests that N. gaeumannii presence and abundance may be related to interactions between host and location.

Phytophthora pluvialis is an oomycete that has been isolated from P. menziesii foliage on the PNW coast (Hansen et al. 2015, 2017, Gómez-Gallego et al. 2019). It is also the causal agent of red needle cast, a foliar disease of Pinus radiata (D. Don) in

New Zealand (Dick et al. 2014), where it likely migrated from the PNW (Brar et al.

2018, Tabima et al. 2020). P. pluvialis occasionally causes symptoms in P. menziesii foliage, but they are more cryptic relative to those in P. radiata. Isolations have been

made from both asymptomatic and cast, olive-colored needles (Tabima et al. 2020).

Periodic and geographically patchy P. pluvialis-induced needle cast events have been observed in the PNW (Hansen et al. 2017), suggesting that its prevalence, reproduction, and impact on the host may be highly localized in space and time

(Tabima et al. 2020). In the PNW, the relative abundance of P. pluvialis and N. gaeumannii are inversely correlated when observed on the same tree (Gómez-

Gallego et al. 2019). This effect was particularly pronounced within study sites rather than at the regional level. Reproductive structures of both microorganisms have also been observed emerging from the stomata of the same needle (Gómez-

Gallego et al. 2019). These data suggest that P. pluvialis and N. gaeumannii may be competing for similar resources while still capable of coexistence. No other significant foliar oomycetes have been described in P. menziesii. Although environment, location, and host factors have been shown to influence N. gaeumannii’s impacts, the relationship of this ubiquitous fungus relative to the P. menziesii microbiome has yet to be characterized.

The Douglas-fir Seed Source Movement Trial (SSMT) is a long-term reciprocal transplant provenance study established by the US Forest Service. It is composed of P. menziesii from seed source regions (SSR) throughout Washington

State (WA), Oregon (OR), and northern California (CA) planted at study sites in corresponding locations (Ford et al. 2016, Harrington and St. Clair 2017). The SSMT provides an ideal framework to study how factors related to location and host lineage influence patterns of microbial community composition. Various foliar fungal endophytes have been observed in SSMT sites, including N. gaeumannii

(Wilhelmi et al. 2017, Daniels et al. 2018), but no foliar oomycetes. The coastal SSMT sites, in WA and OR, fall within P. pluvialis’ observed range (Tabima et al. 2020).

Most research on foliar endophytes of P. menziesii has focused primarily on fungi, and have relied either on culturing methods (Bernstein and Carroll 1977, Carroll and Carroll 1978, Daniels et al. 2018), or visual indications of disease (Boyce 1940,

Parker and Reid 1969, Sherwood-Pike et al. 1986, Stone 1987, Hansen et al. 2000,

Wilhelmi et al. 2017, Samek et al. 2019) when characterizing communities. This study employs both culture-based and next-generation sequencing (NGS) approaches to provide comprehensive descriptions of fungal and oomycete communities (Lindahl et al. 2013).

The primary aim of this study was to characterize and analyze community dynamics of foliar fungi and oomycetes of P. menziesii on the PNW coast. The specific objectives of this study were: 1) describe the foliar fungi and oomycete communities of P. menziesii along the PNW coast; 2) characterize microbial communities in response to effects of host location and lineage; 3) Model fungal diversity in relation to climate transfer distance and oomycete diversity; and 4) investigate any associations between the presence of N. gaeumannii and the presence of oomycetes. These objectives were met by a one-time sampling of trees at the three coastal sites of the SSMT.

Materials and Methods

Study sites

Pseudotsuga menziesii foliage samples were collected from three SSMT common gardens. The SSMT has nine common gardens (sites) located along three latitudinal transects in the PNW. Each common garden has P. menziesii trees from

12 seed source regions throughout the PNW of the United States. Open-pollinated seeds were collected from five P. menziesii dominated stands in each seed source region (Fig. 2.1). Within each stand, seeds were collected from two maternal trees located at least 100 m from each other to reduce the likelihood of their relatedness while still representing similar climate, elevation, and aspect (Wilhelmi et al. 2017)

(Fig. 2.1). Each group of half-siblings from the same maternal tree was considered a family (10 families per seed source region). Seeds were germinated in 2007 and transplanted to the sites after two growing seasons (Ford et al. 2016). The trees were approximately 10 years old at the time of sampling.

Sites were surrounded by commercial even-age P. menziesii stands, fenced to reduce browsing, and had their understories managed to reduce competition

(Harrington and St. Clair 2017). Each site consisted of four blocks that were each divided into 12 sections (plots). Seed source region was randomly assigned to each plot within a block. Plots consisted of 20 trees planted in a 3.6 m x 3.6 m spacing, each family replicated twice in each plot (Fig. 2.2).

Sample collection

To maximize the likelihood of recovering oomycetes from needles, this study focused its efforts on the wet, mild coastal region of the PNW. The three coastal

SSMT sites were selected for sample collection: Jammer in WA (46.749, -124.042),

Nortons in northern OR (44.664, -123.687), and Floras in southern OR (42.904, -

124.356). Within these sites, three coastal seed source regions were chosen: WA coast (WACST), northern OR coast (ORCSTN) and southern OR coast (ORCSTS) (Fig.

2.1). From each of the three seed source regions five families were randomly selected. Needles were sampled from approximately 10 trees per plot. Plots occasionally contained dead or missing trees or more than two replicates per family.

As a result, the total number of trees sampled was n = 338.

Foliage samples were collected between mid-April and late May 2019 to improve the likelihood of recovering foliar oomycetes during the rainy and humid spring weather of the PNW coast (Hansen et al. 2017). Sampling efforts focused on needles that were likely to soon be cast to target potentially pathogenic oomycetes such as Phytophthora pluvialis (Gómez-Gallego et al. 2019). Accessible branches on four sides of each tree were shaken by hand. Approximately 30 cm below the branches a 20.3 x 25.4 cm plastic board was held. All cast needles that landed on the board were placed into a plastic bag. Bags were stored at 4°C for a maximum of 48 hours before being processed.

Twenty needles were then haphazardly selected from each bag. Only needles with living green tissue were selected (Fig. 2.3). These needles were surface

sterilized in a 5% household bleach (NaClO) solution for 30 sec, followed by two 30 sec washes in deionized water, and then air dried. Half the needles (n = 10) were stored at -80°C for 2-3 months prior to DNA extraction and sequencing. The remaining 10 needles were used to isolate endophytic oomycetes.

Culturing and sequencing oomycetes

Needles selected for culturing were plated in CARP, an oomycete-semi- selective agar media (cornmeal agar amended with 20 ppm Delvocid [50% natamycin], 200 ppm Na-ampicillin, and 10 ppm rifamycin SV) (Reeser et al. 2011)

(Fig. 2.4A). Plates were incubated in the dark at 20°C and examined at approximately 7, 10, and 14 days after initial plating. Hyphal tips of oomycetes growing out of the needles (Fig 2.4B) were transferred to cornmeal agar plates for confirmation of purity, characterization, and storage. Cornmeal agar plugs colonized by oomycetes were stored in tubes at room temperature in sterile deionized water with and without hemp seeds (Reeser et al. 2011). Isolates on cornmeal agar (Fig.

2.5) were examined at 100x magnification. Presence of oogonia, antheridia, and oospores confirmed the presence of oomycetes (Fig. 2.6).

Plugs from colonized cornmeal agar were placed in plates of carrot broth, incubated in the dark at 20°C, and examined at approximately 7, 10, and 14 days.

After ample mycelia emerged from the plugs, plate contents were poured through

Miracloth (Sigma-Aldrich, St. Louis, MO, USA) and 40-70 mg of mycelia were scraped into tubes using sterilized scalpels. DNA was extracted using the Thermo KingFisher

Flex system (Thermo Fisher Scientific, Waltham, MA, USA) at the Center for Genome

Research and Biocomputing (CGRB) (Oregon State University, Corvallis, OR, USA).

Three genomic regions were amplified from each oomycete: the internal transcribed spacer region (ITS) rDNA, cytochrome c oxidase subunit I (COI) mDNA, and ribosomal protein S10 (rps10) mDNA. ITS amplification was performed using

ITS5 and ITS4 primers (White et al. 1990) (Table 2.1A) on an Applied Biosystems

2720 Thermal Cycler (Thermo Fisher Scientific) (2.5 µL REDTaq® [1U/µL] [Sigma-

Aldrich, St. Louis, MO, USA], 4 µL dNTPs [2.5 mM], 5 µL 10X buffer, 0.5 µL 5%

blocking powder, 34 µL H2O, 2 µL of each primer [10 µM], and 1 µL template DNA) under the following conditions: 94°C for 1 min; 35 cycles of 94°C for 1 min, 55°C for

1 min, and 72°C for 1 min; followed by 72°C for 7 min and 24°C for 1 min. COI amplification was performed using OomCoxI-Levup and OomCoxI-Levlo primers

(Robideau et al. 2011) (Table 2.1A) on an Applied Biosystems 2720 Thermal Cylcer

(2.5 µL REDTaq® [1U/µL], 4 µL dNTPs [2.5 mM], 5 µL 10X buffer, 34.5 µL H2O, 2 µL of each primer [10 µM], and 1 µL template DNA) under the following conditions:

95°C for 2 min; 35 cycles of 95°C for 1 min, 55°C for 1 min, and 72°C for 1 min; followed by a final elongation step at 72°C for 10 min. Rps10 amplification was performed using Prv9r-M and Prv9f-M primers (Foster 2020) (Table 2.1A) on an

Applied Biosystems 2720 Thermal Cycler (0.125 µL GenScript Taq [5U/µL]

[GenScript, Piscataway, NJ, USA], 0.5 µL dNTPs [10mM], 2.5 µL 10X Taq buffer with

Mg2+, 1.5 µL MgCl2 [25 mM], 16.9 µL H2O, 1.3 µL of each primer [10 µM], and 1 µL template DNA) under the following conditions: 94°C for 3 min; 35 cycles of 94°C for

30 sec, 55°C for 45 sec, and 72°C for 45 sec; followed by 72°C for 7 min and held at

10°C. All PCR reactions contained two negative controls of all reagents mixed with

deionized H2O instead of template DNA.

PCR products were visualized on a 1% agarose gel, purified using PureLink™

PCR Purification Kits (Invitrogen, Carlsbad, CA, USA), and quantified using Qubit HS dsDNA Assay Kit with a Qubit Fluorometer (Invitrogen). The purified PCR products were sent to the CGRB for Sanger sequencing.

Consensus sequences of all isolates for all genomic regions were assembled in Geneious 2020.1.2 (Biomatters, Ltd., San Diego, CA, USA). Consensus sequences of

ITS and COI were subject to BLAST searches of the NCBI GenBank database. Both searches suggested that all sequences belonged to a species in the genus Pythium. To obtain relevant reference sequences for gene alignment, COI and ITS Pythium spp.

PopSets were extracted from the NCBI database. Consensus sequences of each gene were aligned using MAFFT 7.0 (Katoh et al. 2019). COI sequences aligned to PopSet

985768803 (Coffua et al. 2016) and the gene’s top 10 BLAST search hits in GenBank.

ITS sequences were aligned to PopSet 505574757 (Robideau et al. 2011) and the gene’s top 10 BLAST search hits in GenBank. Rps10 sequences were aligned to all

Pythium entries in the oomycete rps10 database (Martin et al. 2020). Maximum likelihood (ML) trees were generated in the MPI version of RAxML 8.0 (Stamatakis

2014), using a rapid analysis of 100 bootstraps with the GTRGAMMAI model of nucleotide substitution. ML trees were visualized using FigTree 1.4.4 (Rambaut

2012).

Sequencing fungal and oomycete communities

Ten surface sterilized needles were lyophilized then homogenized with glass beads for 1 min in a 2010 Geno/Grinder® Plant and Tissue Homogenizer (SPEX

SamplePrep, Metuchen, NJ, USA) set at 1500 rpm. Total DNA was extracted from 40 mg of homogenized needles using the 96 Well Synergy™ Plant DNA Extraction Kit

(OPS Diagnostics, Lebanon, NJ, USA). The plates of extracted DNA were covered in parafilm and stored at -80°C for 4-5 months prior to sequencing.

For the fungal communities, libraries were prepared for Illumina MiSeq using dual-indexed two stage PCR. The internal transcribed spacer unit 2 (ITS2) rDNA region was targeted using modified versions of the forward primer 5.85S-Fun and reverse primer ITS4-Fun (Taylor et al. 2016). Each primer was merged with

Illumina forward and reverse overhang adapters offset by 3-6 bp heterogeneity spacers (Jensen et al. 2019) (Table 2.1B). Stage 1 PCR was performed on a Nexus

Gradient 6331 thermal cycler (Eppendorf, Hamburg, Germany) (12.5 µL MyFi™ Mix

[Bioline, Memphis, TN, USA], 9 µL H2O, 1.25 µL of each primer mix [10 µM], and 4 µL template DNA). The PCR conditions were 95°C for 3 min; 35 cycles of 95°C for 30 sec, 58°C for 30 sec, and 72°C for 30 sec; followed by 72°C for 3 min and held at 4°C.

One negative control of MyFi™ Mix and primers mixed with deionized H 2O was included on each plate. Gel electrophoresis was performed with 1% agarose gel to visualize the PCR products. For stage 2 PCR, P5 and P7 Illumina primers and 8-mer multiplexing barcodes (Hamady et al. 2008) were added to target the Illumina adapters (Table 2.1B). Stage 2 PCR was performed on a Nexus Gradient 6331

thermal cycler (Eppendorf) (12.5 µL MyFi™ Mix, 9 µL H2O, 1.25 µL of each primer

[10 µM], and 1 µL PCR product) with the following conditions: 95°C for 3 min; 8 cycles of 95°C for 30 sec, 55°C for 30 sec, and 72°C for 30 sec; followed by 72°C for 2 min. Libraries were purified and concentrations normalized using Just-a-Plate™ 96

PCR Purification and Normalization Kits (Charm Biotech, San Diego, CA, USA). The libraries were then concentrated using a SpeedVac Vacuum Concentrator (Thermo

Fisher Scientific, Waltham, MA, USA). Concentrated libraries were resuspended in a

10 mM Tris-HCl buffer. Final libraries were then pooled in equimolar concentrations and sequenced on an Illumina MiSeq 3000 with 300-bp paired end reads at the

Center for Genome Research and Biocomputing (Oregon State University, Corvallis,

OR, USA).

For oomycete communities, the ribosomal protein S10 (rps10) mDNA region was targeted using a nested PCR with degenerate primers. Two forward rps10 primers (rps10_F_Conserved and rps10_F2_Conserved) and seven reverse rps10 primers (rps10_R1 through rps10_R7) (Foster 2020) were used (Table 2.1B). All primers were ligated to Illumina forward and reverse overhang adapters. Primers were added with final concentrations of 0.2 µM, except rps10_F_Conserved which had a single degenerate base, representing two primers. It was added with a final concentration of 0.4 µM (Foster 2020). Amplification was performed using an

Applied Biosystems 2720 thermal cycler (17.5 µL Type-It Multiplex PCR Master Mix

[Qiagen, Germantown, MD, USA], 7 µL H2O, 3.5 µL primer mix, and 7 µL DNA template) under the following conditions: 95°C for 5 min; 35 cycles of 95°C for 30 sec, 58°C for 3 min, and 72°C for 30 sec; followed by 60°C for 30 min then held at

10°C. Gel electrophoresis, stage 2 PCR, library purification, normalization, concentration, pooling, and sequencing were performed in an identical manner to the fungi described above. Fungi and oomycetes were sequenced on the same

Illumina lane, making possible direct comparisons between the two communities.

Bioinformatics

The bioinformatics pipeline was adapted from Leopold and Busby (2020).

Both fungi and oomycetes were demultiplexed using Pheniqs 2.0.4 (Galanti et al.

2017) with a Phred-adjusted maximum likelihood confidence threshold set to 0.995.

Primers and heterogeneity spacers were trimmed from the 5’ ends of the paired reads using cutadapt 2.8 (Martin 2011). Read-through adapter contamination at the

3’ ends was removed using SeqPurge (Sturm et al. 2016). Trimmed reads were filtered with a maximum expected error rate of 2 bp, denoised, merged, and rid of chimeras using the R package DADA2 (Callahan et al. 2016).

The ITS2 region was extracted from the fungal amplicon sequence variants

(ASVs) using ITSx (Bengtsson‐Palme et al. 2013), limiting the search to fungi and higher plant organisms and setting the E-value cutoff to 1e-2 before filtering very short reads under 50 bp in length. Predicted taxonomic classifications were assigned to fungal ASVs using “assignTaxonomy” (DADA2) with the UNITE 8.2 fungi release (Abarenkov et al. 2020b) as the reference database. Non-fungal reads were removed by filtering ASVs against the UNITE 8.2 eukaryote release (Abarenkov et al.

2020a) using the “--usearch_global” option in VSEARCH 2.15 (Rognes et al. 2016).

The pairwise identity threshold was set to 0.70 and the “--maxaccepts” and “--

maxrejects” heuristics were turned off. All ASVs whose top hits were assigned to non-fungal targets were removed. All ASVs found in negative controls were removed from samples in which they were less or equally abundant in the controls.

Negative controls were then removed from the dataset. All ASVs with zero reported reads were also removed. ASVs were then clustered at 99% similarity with R package DECIPHER (Wright 2016).

Fungal samples with fewer than 1000 reads (n = 90) were removed from further analysis. Singleton OTUs were removed from both datasets. Raw OTU reads were converted to per-sample proportional abundance to normalize differential sequencing depths (McMurdie and Holmes 2014), then transformed with a generalized log transformation (McCune and Grace 2002) to eliminate heterogeneity of variances among groups tested in the subsequent analyses

(Anderson et al. 2008).

Following the DADA2 pipeline, oomycete ASVs were filtered, removing very short reads under 50 bp in length. Taxonomic classifications were similarly predicted using “assignTaxonomy” (DADA2) with oomycete rps10 database (Martin et al. 2020) as the reference. Negative control filtering and ASV clustering was performed in an identical manner to the fungi described above. Oomycete samples with fewer than 500 reads (n = 138) were removed from further analysis. Singleton

OTUs were removed and raw OTU reads were converted to per-sample proportional abundance and log transformed identically to the fungi described above.

This produced two datasets: “fungi” (n = 246, 105 OTUs) and “oomycetes” (n

= 181, 55 OTUs). A third dataset, “microbial,” was produced in order to evaluate and compare diversity of both fungi and oomycetes. Fungi and oomycete datasets were merged prior to filtering samples below a read depth threshold. In this full microbial dataset, all samples with fewer than 1000 reads (n = 54) were removed. Singleton

OTUs were removed. To account for variable sequence depth across samples, OTU richness was rarefied to 1000 minimum reads. This dataset contained n = 282 samples and 157 OTUs (105 fungi and 52 oomycetes).

Statistical analysis

All statistical analyses were performed in R 3.6.3 (R Core Team 2020) unless noted otherwise. Taxonomic composition of fungi was visualized by constructing taxonomic heatmaps using the R package metacoder (Foster et al. 2017).

To test whether community composition of fungi varied with location and tree lineage, permutational analysis of variance (PERMANOVA) was performed on

Bray-Curtis dissimilarity of fungal communities among trees using PERMANOVA+ add-on for Primer 7 (Anderson et al. 2008). Location effects were the random effects site and block nested within site (block[site]). Tree lineage effects were the random effects seed source region (SSR) and family nested within SSR

(family[SSR]). The highest order term (block[site] x family[SSR]) was excluded from the analysis because of a lack of true replication at the family level due to dead or missing trees. To test PERMANOVA’s assumption of homogeneity of dispersions among groups, betadispersion within sites and SSRs was calculated using

“betadisper” in the R package vegan (Oksanen et al. 2019). Differences among groups were tested using Tukey’s honestly significant difference test. Fungal community composition between sites was visualized with distance-based redundancy analyses (db-RDA) of the Bray-Curtis dissimilarity among trees using

“dbrda” in vegan (Oksanen et al. 2019). Site was chosen as the predictor variable because it was a significant term in the PERMANOVA analysis with the largest pseudo-F statistic, indicating the largest effect size.

To examine whether specific fungal OTUs were characteristic of trees between sites, indicator species analysis was performed using the “multipatt” function in the R package indicpecies (Cáceres and Legendre 2009). P-values were corrected for multiple comparisons using the Benjamini-Hochberg Procedure

“p.adjust” in the R package stats (R Core Team 2020). All OTUs with indicator values

≥ 0.3 and adjusted p ≤ 0.05 were reported (Dufrêne and Legendre 1997).

Fungal and oomycete rarefied richness were estimated in the microbial dataset with the Chao1 richness index, prior to removal of singletons, using the

“estimateR” function in vegan (Chao 1984, Oksanen et al. 2019). To test whether fungal and oomycete richness varied by site and SSR, four Kruskal-Wallis rank sum tests were performed using the “kruskal.test” function in the R package stats (R Core

Team 2020). The response variables were either fungal richness or log oomycete richness, and predictor variables were either site or SSR. P-values of individual groups were corrected for multiple comparisons using Dunn’s test with the

“dunnTest” function in the R package FSA (Ogle et al. 2020).

Fungal rarefied richness was then correlated with oomycete rarefied richness and three climate transfer distances, calculated by subtracting a tree’s climate value at its study site from its climate value at its seed collection location.

Mean summer precipitation (MSP), mean winter temperature (MWT), and continentality (TD) were selected because their transfer distances predicted severity of the foliar diseases SNC and Rhabdocline needle cast (RNC) at the SSMT sites (Wilhelmi et al. 2017). Climate data were obtained using ClimateWNA data

(Wang et al. 2012) interpolated for coordinates of seed collection locations and study sites from years 1981-2010. To make direct comparisons, all predictor variables were standardized by subtracting their means and dividing by standard deviation. TD was found to be colinear with MWT and was dropped from the analysis.

Generalized linear mixed models were constructed using the “glmer” function in the R package lme4 (Bates et al. 2014). Four models were fit using a

Poisson distribution because rarefied fungal richness was discrete counts of OTUs

(Zuur et al. 2009). The following models were compared: 1) all variables as predictors (“full model”); 2) only oomycete Chao1 richness as a predictor (“richness model”); 3) only MSP transfer distance and MWT transfer distance as predictors

(“climate model”); and 4) no variables as predictors (“intercept model”). To account for random variation present between locations and genetic variation present between trees, all four models contained four random effects: site, block nested within site, SSR, and family nested in SSR. Model selection was performed to evaluate the relative importance of the microbial and climate variables using the

“model.sel” function in the R package MuMIn (Barton 2020). This method accounts for small sample sizes by comparing models’ second-order Akaike Information

Criterion (AICc) (Burnham and Anderson 2002) and their weights. Marginal R2 values of models’ fixed traits were calculated using “r.squaredGLMM” function in

MuMIn (Barton 2020).

To evaluate the response of the fungus Nothophaeocryptopus gaeumannii to the presence of the dominant oomycete OTU, Phytophthora cacuminis I. Khaliq & T.I.

Burgess, a mixed-effects logistic regression was performed using the “glmer” function in lme4 (Bates et al. 2014). Rarefied presence/absence of the OTU assigned to N. gaeumannii was used as the response variable and rarefied presence/absence of the OTU assigned to P. cacuminis was used as the predictor. The random effects were site and block nested within site. SSR and family nested within SSR were omitted because models failed to converge when they were included.

Results

Oomycete isolates

Eighteen oomycete cultures were isolated from the 338 trees sampled across all sites. Sixteen isolates were recovered from Nortons, two from Floras, and none from Jammer (Table 2.2). After subculturing onto cornmeal agar, four isolates were lost due to contamination. Two of the remaining 14 cultures failed to grow after being transferred to carrot broth. Mycelium from a total of 12 cultures, 11 from

Nortons and one from Jammer, was submitted for DNA extraction and Sanger sequencing.

Isolates on cornmeal agar (Fig. 2.5) were examined at 100x magnification.

Presence of oogonia, antheridia, and oospores confirmed the presence of oomycetes

(Fig. 2.6). BLAST searches of ITS and COI Sanger sequences against the NCBI

GenBank database suggested that all isolates were likely in genus Pythium. ML trees including known Pythium spp. Sequences suggested that the cultures were all undescribed species in the genus Pythium (Fig. 2.8) with all cultures clustering in unique clades with high bootstrap support (COI: 97%, ITS: 100%, rps10: 99%).

These results were consistent in all three sequenced loci.

Community composition of fungi and oomycetes

Following removal of singletons, P. menziesii was host to a moderately diverse community of foliar fungi (105 OTUs). A total of 57% of OTUs were assigned to the phylum Ascomycota and 40% to the phylum Basidiomycota (Fig. 2.9). The majority of the ascomycetes were Dothideomycetes (40%) and Leotiomycetes

(23%). Basidiomycetes were mainly Tremellomycetes (31%), Agaricomycetes

(29%), and Microbotryomycetes (26%) (Fig. 2.9). The three most dominant fungal genera were ascomycetes (Fig. 2.9) and contained well-documented P. menziesii pathogens and endophytes: 1) Rhabdocline spp., comprised of needle endophyte R. parkeri (Stone 1987), and the causal agent of Rhabdocline needle cast R. pseudotsugae (Parker and Reid 1969, Samek et al. 2019); 2) Nothophaeocryptopus gaeumannii, the causal agent of the foliar disease Swiss needle cast (SNC) which is

prevalent along the PNW coast (Hansen et al. 2000, Maguire et al. 2002, Ritóková et al. 2016); 3) Rhizosphaera spp., which contains a variety of species (R. oudemansii, R. pseudotsugae, R. kalkhoffii) that have been commonly observed as endophytes and pathogens in P. menziesii and other conifer species (Butin and Kehr 2000, Winton

2001, Scattolin and Montecchio 2009).

P. menziesii’s oomycete community was smaller than that of fungi, with 55

OTUs. Only six OTUs were assigned to an order: one Peronosporales and five

Pythiales. The Peronosporales OTU was also the lone species assignment in the dataset: Phytophthora cacuminis, a recently described species isolated from asymptomatic Eucalyptus coccifera Hook.f. root tissue in alpine environments of

Tasmania, Australia (Khaliq et al. 2019). Rps10 sequences of the Pythium spp. cultures isolated from P. menziesii needle tissue revealed close matches (97-99% identity, E < 0.01, 638-808 bit score) to OTU 4, a doubleton assigned to order

Pythiales. Exploration of OTU data revealed an oomycete community heavily dominated by the P. cacuminis OTU, which appeared in over 95% of samples (173 out of 181). The remaining 54 OTUs were composed of 27 doubletons and 10 tripletons, resulting in nearly 70% of OTUs appearing only two or three times in the dataset (Fig. 2.7). While doubletons and tripletons made up a considerable portion of the fungal dataset, fungal community composition was less skewed than that of oomycetes. For this reason, some of the community analyses used for fungi were rejected for oomycetes.

Community composition of P. menziesii foliar fungi varied significantly between tree locations. After determining that betadispersion of fungal community dissimilarity did not vary significantly among sites or SSRs, a PERMANOVA test

revealed the largest effect was between sites (F2,254 = 4.2, p = 1.0e-4), followed by

within site variation (F9,245 = 1.8, p = 1.5e-3). Location by tree lineage interactions had small but significant effects on fungal community composition (Table 2.3). Tree lineage appeared to have no relationship to foliar fungi community composition of

P. menziesii (Table 2.3). Visualization of db-RDA constrained by site revealed distinct groups of fungal communities, despite some overlap. Communities in Floras appear to be constrained by axis 1 and those in Nortons constrained by axis 2 (Fig.

2.10).

Indicator species analysis was used to determine whether particular fungal

OTUs were characteristic of the study sites, or vice versa. 15 indicator OTUs were identified with indicator values ≥ 0.3 and Benjamini-Hochberg adjusted p-values ≤

0.05. Three indicator OTUs were characteristic of two sites (Table 2.4, Fig. 2.11).

Fungal diversity in response to biotic and abiotic predictors

Fungal rarefied richness varied significantly by site (Kruskal Wallis H = 49.6, p = 1.7e-11, df = 2), but not SSR (Kruskal-Wallis H = 3.5, p = 0.2, df = 2) (Fig. 2.12A,

B). Similarly, log oomycete rarefied richness varied significantly by site (Kruskal

Wallis H = 12.1, p = 2.3e-3, df = 2) but not by SSR (Kruskal-Wallis H = 0.02, p = 0.99, df = 2) (Fig. 2.12C, D), suggesting that local environmental conditions, rather than trees’ origin, determined microbial community richness. Dunn’s tests of Kruskal-

Wallis ranks sums were performed because the data violated ANOVA assumptions of equal variance and normality.

Fungal rarefied richness was tested in response to biotic and climate variables that have previously been shown to predict presence and severity of foliar fungal pathogens: oomycete rarefied richness, mean summer precipitation (MSP) transfer distance, and mean winter temperature (MWT) transfer distance. AICc scores and weights indicate that oomycete richness is a better predictor of fungal richness than the climate transfer distances (Table 2.5). The richness model had a high AICc weight (0.83) compared to the next-best full model (0.11), and was the only model within a 95% confidence set of models (Zuur et al. 2009). However, the richness model also had relatively low explanatory power (marginal R2 = 0.067).

When modeled as a mixed-effects logistic regression, the presence of N. gaeumannii had an inverse relationship with the presence of the oomycete P. cacuminis (p = 0.03) (Table 2.6). When accounting for the random effects of tree location, the probability of N. gaeumannii being present in a tree when P. cacuminis is present was estimated to be 0.68, while the probability of N. gaeumannii being present in a tree when P. cacuminis is absent was estimated to be 0.80.

Discussion

Foliar fungal communities are structured by local environmental conditions

Variation in foliar fungal communities is determined by local conditions, where the largest effects explained differences among sites, then within sites, and finally the interaction between site and host lineage (Table 2.3). This is consistent with other studies, where geographic distance among sites best explains variation in plants’ foliar endophyte communities, followed by finer-scale differences within sites, then among host genotypes within locations (Hoffman and Arnold 2008,

Zimmerman and Vitousek 2012, Wagner et al. 2016, Ibrahim et al. 2017). The geographic structure of these communities could be explained by spatial limitations in spore dispersal between and even within sites. Dispersal limitation has been shown to be a key process in structuring biogeographical patterns in fungal communities (Peay et al. 2010, Peay et al. 2012, Adams et al. 2013). Distance-decay relationships are present in fungal sporulation, where the likelihood of reaching a host decreases rapidly with increased distance (Peay et al. 2012). Neighboring leaves in a tree canopy are more likely to share endophytic community similarity

(Donald et al. 2020). In this study, sites were separated by hundreds of kilometers and ambient fungal communities were likely unique to each location.

Host lineage may not have had a constitutive effect on community structure because there may not have been meaningful between-group genetic structure in

SSRs when averaged across all three sites. P. menziesii predominantly reproduces via outcrossing and is highly variable in virtually all of its observed traits (Neale et

al. 2017). On the PNW coast, P. menziesii appears to have little to no genetic structure among populations sampled from southern OR to southern British

Columbia (Krutovsky et al. 2009, Müller et al. 2015). It’s possible that the three coastal SSRs exhibited no meaningful between-group genetic variation when averaged across all three sites. However, SSR by location interactions did have small but significant effects in structuring fungal communities. This suggests that any host genetic variation may be differentially expressed depending on environmental conditions, resulting in fungal community variation.

Wagner et al. (2016) propose two non-mutually exclusive explanations for this phenomenon: 1) The extent to which phenotypic plasticity occurs in each host genotype varies from site to site due to environmental differences. This results in site-specific patterns of host trait variation, affecting the associated fungal communities. Some important host traits in this case could include stomatal density, leaf cuticle thickness, or production of secondary metabolites; and 2) Only certain groups of fungi might be affected by host genetic variation, and those groups may be present in varying quantities among the ambient communities at the different sites.

Host genotypic data were not collected in this study. Recent advancements in descriptions of the P. menziesii genome (Howe et al. 2013, Neale et al. 2017, Howe et al. 2020) could open the door to future experiments investigating the host’s control of its microbiome, such as genome-wide association studies of trees inoculated with synthetic microbial communities (Beilsmith et al. 2019, Bergelson et al. 2019).

Several fungal OTUs of diverse taxa were directly associated with the study sites (Table 2.4). Of the three sites, Jammer had the fewest indicator OTUs (Table

2.4), as well as the lowest OTU richness (Fig. 2.12A, C), and the weakest community differentiation from the other sites (Fig. 2.10). Jammer’s lack of a unique community identity and low richness could be explained by its environmental conditions.

Jammer was the most topographically homogenous of the three sites, with a weak slope throughout that allowed for little variation in the amount of wind and sun exposure received by trees. Both Floras and Nortons had a mix of steep, windswept slopes and flat lowlands. The lack of topographical and microclimate variation at

Jammer may have limited variation in host phenotypic plasticity, as suggested above. Jammer also had the most uniformly dense and homogenous understory of the invasive shrub Rubus armeniacus Focke (Himalayan blackberry). In contrast, both Floras and Nortons had more patchy and diverse understories including native plants such as Vaccinium ovatum Pursh (evergreen huckleberry) and Gaultheria shallon Pursh (salal). Ambient fungal communities may have been more uniform throughout Jammer as a consequence of the lack of alternate hosts and microclimate diversity (Saikkonen et al. 2007).

Across all three sites, the most frequently recovered fungal OTUs were well- documented foliar pathogens and endophytes of P. menziesii (Fig. 2.9). The presence of many assigned taxa was reflected in the sampling of newly-cast needles. The most abundant fungal OTU, assigned to R. parkeri, appeared in all but six samples. R. parkeri is an endophyte and latent saprophyte whose sporulation on foliar tissue coincides with needle abscission (Sherwood-Pike et al. 1986, Stone 1987). N.

gaeumannii, the causal agent of a needle casting disease, was another highly abundant OTU recovered from all three sites. SNC has previously been reported in the coastal SSMT study sites (Wilhelmi et al. 2017). Although SNC disease symptoms were not recorded as part of this study, sampled trees appeared largely free of severe SNC symptoms. Less abundant OTUs were also assigned to taxa that have been described as foliar endophytes and pathogens of P. menziesii and other

Pinaceae. These include genera in some of the most abundant orders: Xylariales,

Helotiales, Capnodiales, and Dothideales (Smerlis 1970, Carroll and Carroll 1978,

Sieber‐Canavesi and Sieber 1993, Winton et al. 2001, Talgø et al. 2010) (Fig. 2.9).

It has been conjectured that conifer needles are abscised when endophyte colonization reaches a threshold value, typically with age (Sieber 2007). Premature abscission can occur when infection rates are high. In adverse conditions, such as low light in dense stands, this can be a mutualistic outcome, usefully eliminating needles that are a carbon sink (Cannell and Morgan 1990, Manter et al. 2003, Sieber

2007). N. gaeumannii infection causes needle casting when a high proportion of

needle stomata are occluded by pseudothecia, limiting CO 2 assimilation (Manter et al. 2000). N. gaeumannii exhibits unusual behavior as a pathogen of conifer needles

(e.g. lack of intracellular infection, fruiting bodies that do not erupt from epidermal tissue) (Stone et al. 2008) and has narrow host specificity to Pseudotsuga species

(Stone et al. 2008). It is also a facultative pathogen, occasionally causing disease despite being observed wherever P. menziesii is found (Boyce 1940). Given these traits, it’s possible that N. gaeumannii coevolved with P. menziesii as a mutualistic endophyte that helped the tree maintain a positive carbon budget. Recent changes

in climate and forest management could favor rampant N. gaeumannii growth, disrupting this evolutionary equilibrium, and causing an SNC epidemic in the two organisms’ native range.

Foliar fungal community composition is structured by needle age and position within a tree’s canopy. Cast needles from easily accessible branches 1.5-

2.5m above the ground were collected in this study, but different communities would likely be observed if young, asymptomatic, or differently positioned needles were sampled instead. Needles exhibiting symptoms of disease, such as discoloration and dieback, support more diverse communities of pathogens and saprophytes than healthy needles of the same age class (Millberg et al. 2015).

Symptomatic needles are more likely to be of older age classes than healthy needles.

Foliar fungal communities tend to increase in diversity and abundance as foliage ages and eventually dies (Bernstein and Carroll 1977, Osono and Mori 2004,

Terhonen et al. 2011, U’Ren and Arnold 2016). Variation in leaf position within a canopy can also affect colonization outcomes. Those located closer to each other in the canopy can have more similar endophytic communities (Donald et al. 2020), shade dwelling leaves can be more diverse than those with high sun exposure on the same tree (Unterseher et al. 2007), and community composition can vary with leaves’ vertical positions within a crown (Johnson and Whitney 1989, Osono and

Mori 2004, Harrison et al. 2016). To paint a more comprehensive portrait of P. menziesii’s foliar microbiome, future studies should take into account needle age and position.

Foliar oomycete communities are dominated by one OTU

While fungal communities were well-described and moderately diverse, foliar oomycetes of P. menziesii did not form particularly robust communities. A single dominant OTU was found in nearly every sample and assigned to

Phytophthora cacuminis. P. cacuminis is a heterothallic Clade 9 Phytophthora. It was recently described after being isolated from asymptomatic Eucalyptus coccifera root tissue in alpine environments in Tasmania, Australia (Khaliq et al. 2019). It is unknown whether P. cacuminis is a native or exotic oomycete in Australia, given its recent isolation and narrow geographic range. However, P. cacuminis is likely well adapted to colder environments because of its relatively low optimal growth temperature (15-20°C) compared to other Australian Phytophthora species (20-

30°C) (Khaliq et al. 2019). P. cacuminis produces asexual but not sexual structures in vitro (Khaliq et al. 2019). Low optimal growth temperature and the ability to produce asexual structures are functional traits that can determine the establishment of Phytophthora species in colder environments (Redondo et al.

2018).

The SSMT study sites have average spring and summer temperatures in the range of 9-18°C. N. gaeumannii, another common foliar endophyte, has optimal sporulation and growth temperatures of 18°C and 22°C, respectively (Capitano

1999). These temperatures overlap with P. cacuminis’s optimal growth temperatures in vitro, suggesting that the PNW coast could be an ideal habitat. Its presence in the PNW would be yet another example of long-distance migration of a

forest Phytophthora between the PNW and Oceania (Brar et al. 2018, Tabima et al.

2020). Future isolation of P. cacuminis throughout the SSMT sites is required to confirm its presence in the PNW.

Despite establishing sampling efforts to target P. pluvialis and other oomycetes, OTUs assigned to P. pluvialis were present in only a single sample from

Jammer. Because singletons were removed from the dataset, its presence was documented but not included in most downstream analyses. Its omission from most samples was noteworthy because previous studies have had considerable success in isolating P. pluvialis from cast P. menziesii needles in the PNW (Hansen et al. 2017,

Brar et al. 2018, Gómez-Gallego et al. 2019, Tabima et al. 2020). It’s possible that the primers used here for NGS were inappropriate for amplifying rps10 in P. pluvialis.

However, no P. pluvialis isolates were recovered by culturing cast P. menziesii needles using the same methods employed in previous studies (Reeser 2013,

Hansen et al. 2017, Gómez-Gallego et al. 2019), corroborating the NGS results. P. pluvialis proliferates in episodic and geographically isolated epidemics in the PNW

(Hansen et al. 2017, Tabima et al. 2020), indicating that its disease symptoms may be highly localized and regulated by environmental conditions. It’s possible that this study’s sampling region and timing were not conducive to the recovery of P. pluvialis.

While P. pluvialis was not isolated from the SSMT sites, 18 Pythium isolates were recovered. All 18 isolates were closely related to each other (Fig. 2.8) and were closely matched to a doubleton OTU in the NGS dataset assigned to the family

Pythiaceae. The two samples containing this OTU were present in a Nortons plot from where two of the isolates were recovered. Multiple Pythium species have been isolated from forest soils, tree nursery soils, and tree seedlings in the PNW and abroad (Dumroese and James 2005, Augspurger and Wilkinson 2007, Weiland

2011). Pythium species have been associated with damping-off, root lesions, and root rot of P. menziesii seedlings (Weiland et al. 2013). Pythium dissotocum, P. irregulare, P. mamillatum, and P. sylvaticum are all species associated with forest disease (Weiland et al. 2014), but did not appear closely related to the Pythium isolates in this study when aligned to any of the sequenced genes (Fig. 2.8). Many species of Pythium are not plant pathogens, so the identification of isolates to this genus is not sufficient to determine risk of disease (Redekar et al. 2019). Further studies in growth habit, reproduction, and inoculation of seedlings should be conducted to further describe these isolates’ morphology, behavior, and functional traits.

Presence of foliar fungi can be predicted by the presence of foliar oomycetes

Fungal richness responded positively to oomycete richness but not to host trees’ MSP and MWT transfer distances (Table 2.5). This builds on Wilhelmi et al.

(2017), who observed that various measures of disease severity of both SNC and

RNC in the SSMT plots had strong relationships to trees’ MSP, MWT, and/or continentality transfer distances. The results presented here suggest that climate transfer distances cannot predict all measures of fungal presence and that SNC and

RNC severity may not be coupled with a tree’s foliar fungal richness. A lack of large

variation in climate transfer distances between the three coastal SSRs could also explain this lack of signal. Wilhelmi et al. (2017) sampled from every tree from all

12 SSRs at each of the nine SSMT sites. Their study included trees with dramatic climate transfer distances between a relatively mild coastal region and more continental mountainous regions. Because this study was limited to trees and sites with similar coastal climates, climate transfer distances may not have been sufficiently variable enough to predict differences in fungal richness in P. menziesii needles. It’s also important to note that while significant, oomycete richness had relatively low explanatory power with its small marginal R2 (Table 2.5), suggesting that while more statistically appropriate than climate transfer distances, oomycete richness was not a particularly useful variable for predicting foliar fungi richness among trees in coastal sites from coastal SSRs.

Presence of N. gaeumannii in a tree was inversely correlated to the presence of P. cacuminis (Table 2.6). This resembles the negative correlation of N. gaeumannii and P. pluvialis relative abundance in P. menziesii needles in the PNW (Gómez-

Gallego et al. 2019). It’s possible that, as has been proposed for N. gaeumannii and P. pluvialis, a long period of sympatry and competition between both microorganisms in the PNW has resulted in some degree of niche differentiation within or between trees (Abdullah et al. 2017, Gómez-Gallego et al. 2019). Like Gómez-Gallego et al.’s

(2019) results, many samples (43%) contained both N. gaeumannii and P. cacuminis

(Fig. 2.13). Because 10 needles from each tree were pooled for DNA extraction, it’s impossible to know whether segregation occurred at the needle level.

P. cacuminis has previously only been isolated from Eucalyptus coccifera root tissue (Khaliq et al. 2019), so there is no indication as to how it might be colonizing

P. menziesii needles. Given its limited reports, it’s also unclear whether it’s endemic to Australia, the PNW, or elsewhere. P. pluvialis infects leaf tissue when zoospores reach needle surfaces via water splash, where they encyst and colonize intercellular space (Gómez-Gallego et al. 2019). Sporangia emerge from stomatal openings where sporulation occurs again (Dick et al. 2014, Gómez-Gallego et al. 2019). Fruiting bodies of both N. gaeumannii and P. pluvialis have been observed emerging from stomata on the same needle (Gómez-Gallego et al. 2019). No P. cacuminis inoculation experiments have been reported, so its method of needle colonization is unknown and cannot be speculated upon. Collection of physical P. cacuminis specimens from

SSMT sites could confirm its presence in the PNW and allow for further exploration of its apparent colonization of P. menziesii needles. This could clarify the ecology of

P. cacuminis and N. gaeumanni to help understand whether they compete directly or occupy different niches within needle tissue.

Conclusions

Foliar fungal communities of P. menziesii vary at different scales through space, largely influenced by site, then within site, then with location by SSR interactions. Fungal communities were composed of taxa that have previously been documented in P. menziesii and other conifer foliage, as well as others that have never before been isolated in culture from P. menziesii needles. Oomycete

communities across all three sites were dominated by a single OTU, Phytophthora cacuminis, a species previously reported only in asymptomatic Eucalyptus roots in

Australia. While oomycete communities were not particularly diverse, their richness was directly correlated to fungal richness in the same trees. This predicted fungal richness more strongly than trees’ climate transfer distances, which have previously been shown to predict foliar disease severity throughout the SSMT. This suggests that severity of foliar fungal diseases may not be tightly paired to overall fungal richness. Furthermore, the presence of P. cacuminis in a tree predicted the absence of N. gaeumannii, a result that reflects previously observed measures of inverse abundance between N. gaeumannii and another oomycete, P. pluvialis. Altogether, these results suggest that community composition of foliar fungi and oomycetes of

P. menziesii is regulated by local environmental conditions.

This study provides greater understanding of foliar microbial communities of

P. menziesii in its native PNW coast environment. This is the first recorded study to use NGS to characterize P. menziesii’s foliar microbiome, and the first to consider non-pathogenic oomycetes. This has expanded the understanding of P. menziesii’s foliar community composition, the structuring of communities by biotic and abiotic variables, and interkingdom interactions. This is also the first account of a newly described oomycete, P. cacuminis, outside of Australia.

To achieve more comprehensive insights into the effects of location, climate, and host on foliar communities, further research should consider expanding the geographic range of sites and SSRs to allow for more between-group climate and

genetic variation. Recent descriptions of the P. menziesii genome could allow for future studies of specific genes that modulate patterns of community assembly.

Finally, it’s imperative to continue investigating the presence, role, and origins of P. cacuminis in the PNW. This would entail experiments in isolation and inoculation, as well as phylogenetic analyses of specimens from the PNW and Australia.

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Figures

Figure 2.1 Locations of seed source region (SSR) (left) and study sites (right). Seed was collected from 2 maternal trees (inset) in each of 5 locations within each SSR. Each SSR was composed of 10 lines of half-siblings (families). Adapted from Wilhelmi et al. (2017).

Figure 2.2 Example of study site layout. Each site was divided into 4 blocks, where each SSR was randomly assigned a plot. Each SSR plot contained 2 replicates of the 10 families. 5 families were randomly selected for sampling, making a total of 10 samples per SSR plot (inset).

Figure 2.3 Example of needles selected for culturing and DNA extraction. Only cast needles with living green tissue were selected.

Figure 2.4 A 10 needles from a sample plated in CARP. B Pythium mycelia emerging from a needle plated in CARP.

Figure 2.5 Pythium mycelia growing in cornmeal agar.

Figure 2.6 Microscopic image at 100x magnification of Pythium mycelia and reproductive structures. Oogonia with attached antheridia (circled in red) indicate the presence of a homothallic species.

Figure 2.7 Bar graph of the proportion of doubleton, tripleton, etc. OTUs present in the oomycete dataset. Over 50% of OTUs appeared in 2 or 3 samples. One OTU, assigned to P. cacuminis appeared in the overwhelming majority of samples (173 out of 181) and was therefore the only oomycete OTU considered in downstream analyses.

Figure 2.8 ML trees of Pythium isolate genes aligned to three corresponding databases. A COI; B ITS; and C rps10. Isolates are circled in red and known pathogens of P. menziesii seedlings are indicated with blue arrows.

Figure 2.9 Heatmap of all fungal OTUs assigned to a taxonomic group across all three sites. Node width and color indicate log proportional abundance of sequence reads assigned to a given taxonomic group. Dothideomycetes and Leotiomycetes within Ascomycota were the most commonly observed taxonomic groups.

Figure 2.10 Distance-based redundancy analysis (db-RDA) ordination of foliar fungal communities constrained by site based on Bray-Curtis dissimilarity. Each point represents the fungal community of a single tree’s pooled needles. Axes scores show the percentage of total cumulative variation explained by that axis, for a total of about 11.3%.

Figure 2.11 Boxplots of log relative abundance of significant indicator OTUs (Indicator Value ≥ 0.3, BH p ≤ 0.05) at each site. Jammer had one unique indicator OTU, OTU 8, assigned to Penicillium penicillioides.

A B

C D

Figure 2.12 Boxplots of Chao rarefied richness estimates of A fungal OTUs by site; and B fungal OTUs by SSR; and log-transformed Chao rarefied richness estimates of C oomycete OTUs by site; and D oomycete OTUs by SSR. Fungal richness was significantly different (Dunn’s test of Kruskal Wallace rank sums) between all three sites, and oomycete richness was significantly lower at Jammer compared to Nortons and Floras. SSR did not appear to confer any significant difference in OTU richness among fungi or oomycetes.

Figure 2.13 Venn diagram of N. gaeumannii and P. cacuminis presence in samples. 139 out of 282 samples (49%) exclusively contained one OTU or the other.

Tables

Marker Primer Name Primer Sequence (5' → 3') Amplicon Size (bp) ITS5 GGAAGTAAAAGTCGTAACAAGG A ITS 800-900 ITS4 TCCTCCGCCTTATTGATATGC OomCoxI-Levup TCAWCWMGATGGCTTTTTTCAAC COI 700-750 OomCoxI-Levlo CYTCHGGRTGWCCRAAAAACCAAA Prv9r-M GTTGGTTAGAGYARAAGACT rps10 554 Pvr9f-M RTAYACTCTAACCAACTGAGT

Marker Primer Name Primer Sequence (5' → 3') TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG1 NNN→NNNNNN2 B ITS4-Fun CCTCCGCTTATTGATATGCTTAART3 ITS2 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 NNN→NNNNNN2 5.85S-Fun CTTTYRRCAAYGGATCWCT5 rps10_F_Conserved TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG1 GTTGGTTAGAGYAAAAGACT6 rps10_F2_Conserved TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG1 GTTGGTTAGAGTAGAAGACT6 rps10_R1 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 ATGCTTAGAAAGATTTGAACT7 rps10_R2 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 ATACTTAGAAAGATTTGAACT7 rps10 rps10_R3 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 ATGCTTAGAAAGACTTGAACT7 rps10_R4 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 ATGCTTAGAAAGACTCGAACT7 rps10_R5 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 ATGCCTAGAAAGACTCGAACT7 rps10_R6 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 ATGTTTAGAAAGATTCGAACT7 rps10_R7 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG4 ATGCTTAGAAAGATTCGAACT7

1 Forward 5' Illumina overhang adapter 5 ITS2 locus-specific reverse primer 2 3-6 bp heterogeneity spacers 6 rps10 locus-specific forward primer 3 ITS2 locus-specific forward primer 7 rps10 locus-specific reverse primer 4 Reverse 5' Illumina overhang adapter

Table 2.1 Primers used in gene amplification. A Amplicon primers for oomycete isolate sequencing; and B amplicon primers, Illumina adapters, and heterogeneity spacers used for Illumina sequencing of fungal and oomycete communities.

Isolate ID Site Family ID Seed Source Region Sequenced N4-3180-1744 Nortons 3180 ORCSTS y N4-6059-2800 Nortons 6059 ORCSTS n N11-3147-1660 Nortons 3147 ORCSTN y N11-3147-6494 Nortons 3147 ORCSTN n N11-6021-2578 Nortons 6021 ORCSTN y N13-3147-6436 Nortons 3147 ORCSTN n N15-7202-3652 Nortons 7202 WACST y N22-8528-9066 Nortons 8528 ORCSTS y N26-3180-6525 Nortons 3180 ORCSTS y N26-8528-4464 Nortons 8528 ORCSTS y N32-3148-6502 Nortons 3148 ORCSTN n N32-6021-2581 Nortons 6021 ORCSTN y N32-8525-4418 Nortons 8525 ORCSTN n N32-8525-9030 Nortons 8525 ORCSTN y N36-8027-8820 Nortons 8027 WACST y N42-7206-8413 Nortons 7206 WACST y J3-8046-8957 Jammer 8046 ORCSTN n J20-7206-3727 Jammer 7206 WACST y

Table 2.2 Oomycete isolates collected and sequenced from the SSMT sites. Some isolates were lost to contamination or failed to grow in liquid media and were not sequenced.

Source df SS MS Pseudo-F P (perm) Site 2 30432 15216 4.2251 0.0001 SSR 2 5081.4 2540.7 1.2531 0.1455 Block(Site) 9 20881 2320.1 1.7918 0.0015 Family(SSR) 12 17379 1448.2 1.0818 0.3233 Site x SSR 4 6938.5 1734.6 1.0433 0.0238 Site x Family(SSR) 24 32811 1367.1 1.4032 0.0008 Block(Site) x SSR 18 23497 1305.4 1.3398 0.0064 Residuals 174 1.69E+05 974.29 Total 245 3.11E+05

Table 2.3 PERMANOVA results of location and host lineage effects on fungal communities, measured as Bray-Curtis dissimilarity. Location effects: Site, Block nested in Site. Host lineage effects: SSR, Family nested in SSR. The highest order term (Block[Site] x SSR[Family]) was excluded because it lacked replication at the lowest level due to dead or missing trees throughout the sites.

OTU ID Indicator Value p-value Site Taxonomic Group OTU.7 0.65 0.0009 Floras + Nortons Cladosporium sp. OTU.12 0.63 0.0009 Jammer + Nortons Didymellaceae OTU.21 0.58 0.0009 Nortons Rasutoria tsugae OTU.9 0.54 0.0009 Floras Hormonema macrosporum OTU.16 0.52 0.0009 Floras Perusta inaequalis OTU.19 0.51 0.0009 Nortons Venturia sp. OTU.8 0.49 0.0009 Jammer Penicillium penicillioides OTU.10 0.47 0.0009 Floras Curvibasidium cygneicollum OTU.13 0.44 0.0009 Nortons Dermateaceae OTU.22 0.44 0.0009 Floras Tremellales OTU.24 0.44 0.009 Floras Krasilnikovozyma huempii OTU.60 0.35 0.0009 Nortons Xylariales OTU.83 0.34 0.002 Floras Mycosphaerellaceae OTU.87 0.32 0.004 Nortons Capnodiales OTU.28 0.3 0.046 Floras + Nortons Krasilnikovozyma huempii

Table 2.4 Indicator values, Benjamini-Hochberg adjusted p-values, and assigned taxonomic groups of indicator OTUs in each site. Only OTUs with indicator values ≥ 0.3 and p ≤ 0.05 were reported (Dufrêne and Legendre 1997).

Model Intercept Oo richness MSP MWT df AICc ΔAICc AICc weight R2m Richness 1.81 0.135 -- -- 6 1743.1 0 0.83 0.067 Full 1.81 0.134 0.024 0.13 8 1746.3 3.2 0.17 0.11 Intercept 1.82 ------5 1794.4 51.3 0 0 Climate 1.82 -- 0.0075 0.21 7 1797.5 54.4 0 0.1

Table 2.5 Model selection table of four generalized linear mixed models with fungi richness as response. Random effects: Site, Block(Site), SSR, Family(SSR). The richness model, with AICc weight = 0.83, is the only model to fall within a 95% confidence interval (Zuur et al. 2009).

Term Estimate Std Error z value p Intercept 1.393 0.458 3.047 0.002 P. cacuminis -0.654 0.309 -2.117 0.03

Table 2.6 Output of mixed-effect logistic regression of P. gaeumannii presence/absence as response. Random effects: Site, Block(Site). SSR and Family(SSR) were omitted as random effects because models failed to converge when they were included. 86

Chapter 3: General Conclusions

This is the first reported study to use NGS to characterize the foliar fungal and oomycete microbiomes of Pseudotsuga menziesii, as well as one of the few to attempt to isolate and characterize oomycetes from P. menziesii foliage in its native range (Hansen et al. 2017, Gómez-Gallego et al. 2019). This builds on previous studies that have taken culture- and symptom-based approaches to describe the composition of these communities (Boyce 1940, Bernstein and Carroll 1977, Carroll and Carroll 1978, Sherwood-Pike et al. 1986, Daniels et al. 2018), which are biased toward culturable non-obligate endophytes and pathogens. The results presented here contribute to a more comprehensive understanding of the microbial communities inhabiting P. menziesii foliar tissue.

Foliar fungal communities were found to be moderately diverse, containing many taxa that have been previously identified in P. menziesii and other conifer tissue (Boyce 1940, Parker and Reid 1969, Bernstein and Carroll 1977, Carroll and

Carroll 1978, Sherwood-Pike et al. 1986, Butin and Kehr 2000, Scattolin and

Montecchio 2009, Talgø et al. 2010, Daniels et al. 2018), as well as many novel taxa.

Foliar fungal communities were structured by a spatial hierarchy: most variation in community composition was explained by between-site differences, followed by within-site, then location by host lineage interactions. This closely tracks with the literature of endophytic community assembly, which generally find that spatial and climate effects most strongly structure foliar microbial communities, followed by location by host genotype interactions, and sometimes host genotype (Hoffman and 87

Arnold 2008, Zimmerman and Vitousek 2012, Millberg et al. 2015, Solis et al. 2016,

Wagner et al. 2016, Ibrahim et al. 2017, Bowman and Arnold 2018).

Explanations for these strong spatial effects have been attributed to significant dispersal limitation of spores (Peay et al. 2010, 2012, Adams et al. 2013,

Donald et al. 2020), environmental filtering of fungal communities (Kivlin et al.

2014), and variation in site to site interactions between phenotypic plasticity and ambient microbial communities (Wagner et al. 2016). This study did not investigate any mechanisms of spatial versus host lineage effects on foliar community structure.

Future research could address this by increasing both geographic distance between sites as well as genetic distance between hosts to maximize variation (Wilhelmi et al. 2017), record fine scale measures of site topography and climate to partition spatial and environmental effects on community composition (Barge et al. 2019), or take advantage of recent descriptions of the P. menziesii genome (Howe et al. 2013,

2020, Neale et al. 2017) to investigate whether specific genes modulate microbiome assembly (Beilsmith et al. 2019, Bergelson et al. 2019).

One oomycete species was isolated in culture and a single oomycete OTU dominated the NGS dataset, which was primarily composed of doubletons, and tripletons. While the cultured oomycete and the dominant OTU were not a genetic match, this suggests that P. menziesii’s foliar oomycete community is relatively depauperate and possibly comprised of fewer species that have specifically coevolved with P. menziesii or conifers in general. This is in contrast to fungi, which contained multiple, widespread species that have only been described in P. menziesii

or conifer foliage, such as Nothophaeocryptopus gaeumannii, Rhabdocline parkeri, and Rhizosphaera spp.

Genetic analyses revealed the cultured oomycete species to be an undescribed species of Pythium, which was matched to a doubleton OTU in the NGS dataset that was assigned to Pythiaceae. Multiple Pythium species have been implicated in damping off, root rot, and root lesions of P. menziesii seedlings

(Dumroese and James 2005, Weiland 2011, Weiland et al. 2013, 2014), but phylogenetic analyses did not reveal close relationships to any of those species.

Further research should record morphological and reproductive characteristics, as well as infection and life cycle behavior on P. menziesii foliage in order to potentially describe a new species as well as assess any potential effects on its host.

The dominant oomycete OTU was putatively assigned to Phytophthora cacuminis, a species recently cultured from asymptomatic Eucalyptus root tissue in alpine environments in Tasmania, Australia (Khaliq et al. 2019). P. cacuminis has a low optimal growth temperature and does not produce sexual structures in vitro

(Khaliq et al. 2019), two traits that, combined with its alpine habitat, suggest it is adapted to cold environments (Redondo et al. 2018). It is not known whether P. cacuminis is endemic to Australia or whether it has been introduced to the region

(Khaliq et al. 2019), and its description in the PNW of North America certainly raises questions about its origins. While its taxonomy was unambiguously assigned, the presence of P. cacuminis in the NGS dataset is not enough to fully quantify is presence in the PNW, especially because it was not recovered in culture despite

appearing in over 95% of samples. It’s possible that CARP was not the appropriate media for isolated P. cacuminis, as Khaliq et al. (2019) reported isolating it in NARH, a cornmeal-based media containing different antibiotics from CARP (Reeser et al.

2011, Simamora et al. 2018). To verify the NGS findings, P. cacuminis cultures should be isolated from the SSMT sites, and inoculation experiments should be conducted to characterize its mode of infection of P. menziesii foliage.

If its presence in the PNW is confirmed via culturing, P. cacuminis would not be the first example of long-distance migration of a foliar forest Phytophthora species across an ocean. P. ramorum, the invasive causal agent of sudden oak death in northern CA and southwestern OR, has undergone at least four global migration events, including from Europe to western North America (Grünwald et al. 2012). P. pluvialis, the invasive causal agent of red needle cast in Pinus radiata in New

Zealand, migrated to the islands at least once from the PNW (Brar et al. 2018,

Tabima et al. 2020). These long-distance migration events were likely facilitated by human movement of water, soil, asymptomatic plant material, or other substances known to harbor oomycete spores (Davidson et al. 2008, Grünwald et al. 2012, Brar et al. 2018). Phylogenetic analyses should be conducted to understand population structure of P. cacuminis in Australia and the PNW, and to understand the directionality of its movement.

The presence of P. cacuminis in a tree negatively predicted the presence of N. gaeumannii in the same tree, which echoes similar results by Gómez-Gallego et al.

(2019), who found inverse relative abundance between N. gaeumannii and P.

pluvialis in trees in the PNW. They posited that this inverse relationship signaled a longer period of sympatry and competition in the PNW compared to New Zealand, where relative abundances of the two microbes had no negative relationship. The negative presence/absence relationship reported here between N. gaeumannii and

P. cacuminis amplifies the need to investigate the origins and timeline of P. cacuminis in the PNW. Co-inoculation experiments could help demonstrate N. gaeumannii and P. cacuminis’ functional relationship.

Richness of trees’ oomycete community positively predicted the richness of their foliar community. This was a significantly stronger relationship than the trees’ climate transfer distances, which have been associated with SNC and RNC severity in the PNW (Wilhelmi et al. 2017). The lack of signal of climate transfer distances could have a number of explanations. Compared to Wilhelmi et al.'s (2017) study, climate distances of both site and SSR were relatively small, and the lack of variation among those groups could have resulted in low predictive power. It’s also possible that overall fungal richness has no bearing on SNC and RNC severity, and that using the same variables to explain the two is a misguided venture. To better understand whether climate transfer distances have any role in fungal community richness, future studies should consider surveying trees and sites from a broader range of climates.

Altogether, this study broadened understanding of P. menziesii’s foliar fungal and oomycete communities. It demonstrated that those communities are spatially structured, and that mutual diversity of fungi and oomycetes is coupled. A novel

species of Pythium was cultured from P. menziesii needles, and a Phytophthora species never described outside Australia was found in large quantities up and down the PNW coast. There is great potential for future research, from developing a deeper comprehension of P. menziesii’s control of its microbiome to confirming the presence and functional traits of two cryptic oomycete species never before described in the region. Given the outsized role foliar diseases play in coastal PNW forestry, the implications for forest management are clear.

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Hansen, E. M., P. W. Reeser, and W. Sutton. 2017. Ecology and pathology of Phytophthora ITS clade 3 species in forests in western Oregon, USA. Mycologia 109:100–114.

Hoffman, M. T., and A. E. Arnold. 2008. Geographic locality and host identity shape fungal endophyte communities in cupressaceous trees. Mycological Research 112:331–344.

Ibrahim, M., T. N. Sieber, and M. Schlegel. 2017. Communities of fungal endophytes in leaves of Fraxinus ornus are highly diverse. Fungal Ecology 29:10–19.

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Wilhelmi, N. P., D. C. Shaw, C. A. Harrington, J. B. St. Clair, and L. M. Ganio. 2017. Climate of seed source affects susceptibility of coastal Douglas-fir to foliage diseases. Ecosphere 8:e02011.

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